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January 2020

Special Issue: Biomedical Imaging and Analysis in the Age of Big Data and Deep Learning

Volume 108, Issue 1

Guest Editors

Special Issue Papers

Scanning the Issue

By J. S. Duncan, M. F. Insana, and N. Ayache

Deep Learning in Ultrasound Imaging

By R. J. G. van Sloun, R. Cohen, and Y. C. Eldar

This article provides an overview of use of deep, data-driven learning strategies in ultrasound systems, from the front-end to advanced applications. The authors discuss the use of these new computational approaches in all aspects of ultrasound imaging, ranging from ideas that are at the interface of raw signal acquisition (including adaptive beam forming) and image formation, to learning compressive codes for color Doppler acquisition to learning strategies for performing clutter suppression.

Deep-Learning-Based Image Reconstruction and Enhancement in Optical Microscopy

By K. de Haan, Y. Rivenson, Y. Wu, and A. Ozcan

This article provides an overview of efforts to advance the field of computational microscopy and optical sensing systems for microscopy using deep neural networks. First, the work overviews the basics of inverse problems in optical microscopy and then outlines how deep learning can be a framework for solving these problems, typically through supervised methods. Then, there is a discussion of use of deep learning to try to obtain single-image super resolution and image enhancement in these data sets.

Machine Learning in PET: From Photon Detection to Quantitative Image Reconstruction

By K. Gong, E. Berg, S. R. Cherry, and J. Qi

This article discusses applications of machine learning to PET, PET-CT, and PET-MRI multimodal imaging. The authors describe the impact of machine learning at both the detector stage and for quantitative image reconstruction. Also discussed are ideas about how a broad array of statistical methods and neural network applications are improving performance of attenuation and scatter correction algorithms, as well as integrating patient priors into reconstructions based on a constrained maximum-likelihood estimator.

Machine Learning for Rapid Magnetic Resonance Fingerprinting Tissue Property Quantification

By J. I. Hamilton and N. Seiberlich

This article provides an overview of current research that combines MRF and machine learning, as well as presents original research demonstrating how machine learning can speed up dictionary generation for cardiac MRF.

Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine Learning

By S. Ravishankar, J. C. Ye, and J. A. Fessler

This article overviews how sparsity, data-driven methods and machine learning have, and will continue to, influence the general area of image reconstruction, cutting across modalities. In general, this contribution looks at progress in medical image reconstruction methods with focus on the two most recent trends: methods based on sparsity or low-rank models, and data-driven methods based on machine learning techniques.

Model-Based and Data-Driven Strategies in Medical Image Computing

By D. Rueckert and J. A. Schnabel

This article provides a historical overview as to how the medical image analysis and computing field has developed, starting with model-based approaches and then evolving to today’s current emphasis on data-driven/deep-learning-based efforts. These concepts are compared, and advantages and disadvantages of each style of work are noted. The authors note that while data-driven, deep-learning approaches often can outperform the more traditional-model-based ideas, the notion of using these techniques in clinical scenarios has led to a number of challenges that are discussed.

Brain Imaging Genomics: Integrated Analysis and Machine Learning

By L. Shen and P. M. Thompson

This article describes applications of novel and traditional data-science methods to the study of brain imaging genomics. There is a discussion as to how researchers combine diverse types of high-volume data sets, which include multimodal and longitudinal neuroimaging data and high-throughput genomic data with clinical information and patient history, to develop a phenotypic and environmental basis for predicting human brain function and behavior.

Comparison of Breast MRI Tumor Classification Using Human-Engineered Radiomics, Transfer Learning From Deep Convolutional Neural Networks, and Fusion Method

By H. M. Whitney, H. Li, Y. Ji, P. Liu, and M. L. Giger

This article reviews progress in using convolutional neural network (CNN)-based transfer learning to characterize breast tumors through various diagnostic, prognostic, or predictive image-based signatures across multiple imaging modalities including mammography, ultrasound, and magnetic resonance imaging (MRI), compared to both human-engineered feature-based radiomics and fusion classifiers created through combination of the features from both domains.

Wireless Capsule Endoscopy: A New Tool for Cancer Screening in the Colon With Deep-Learning-Based Polyp Recognition

By X. Jia, X. Xing, Y. Yuan, L. Xing, and M. Q.-H. Meng

This article overviews and integrates notions of image acquisition and image analysis for use in cancer screening through wireless capsule endoscopy (WCE). Here, machine and deep learning approaches are being developed to assist in automated polyp recognition/detection and analysis that will enhance diagnostic accuracy and efficiency of this procedure that is a critical tool for use in the clinic.

CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer-Assisted Interventions

By T. Vercauteren, M. Unberath, N. Padoy, and N. Navab

This article overviews ideas as to how to incorporate the range of prior knowledge and instantaneous sensory information from experts, sensors and actuators for use in computer-assisted interventions, as well as learning how to develop a representation of the surgery or intervention among a mixed human-AI team of actors. In addition, the design of interventional systems and associated cognitive shared control schemes for online uncertainty awareness when making decisions in the OR or the IR suite is discussed, and it is noted how this is critical for producing precise and reliable interventions.

Scanning Our Past

The earliest years of three-phase power—1891–1893.

By A. Allerhand

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DATA SCIENCE-2020

Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is related to data mining and big data.

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Join the community, search results for author: ieee, found 66 papers, 11 papers with code, instance paradigm contrastive learning for domain generalization.

no code implementations • IEEE Transactions on Circuits and Systems for Video Technology 2024 • Zining Chen , Weiqiu Wang , Zhicheng Zhao , Fei Su , Member , IEEE , Aidong Men , and Yuan Dong

In this paper, we propose an instance paradigm contrastive learning framework, introducing contrast between original features and novel paradigms to alleviate domain-specific distractions.

An Ultralightweight Hybrid CNN Based on Redundancy Removal for Hyperspectral Image Classification

no code implementations • IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024 • Xiaohu Ma , Wuli Wang , Member , IEEE

Simultaneously, for PW-Conv, we design a spectral convolution with redundancy removal (R2Spectral-Conv).

Meta Reinforcement Learning for Multi-Task Offloading in Vehicular Edge Computing

no code implementations • TMC 2024 • Penglin Dai , Yaorong Huang , Kaiwen Hu , Xiao Wu , Huanlai Xing , and Zhaofei Yu , Member , IEEE

The objective is to design a unified solution to minimize task execution time under different MTO scenarios.

Ultra-Robust Real-Time Estimation of Gait Phase

no code implementations • IEEE Transactions on Neural Systems and Rehabilitation Engineering 2023 • Mohammad Shushtari , Hannah Dinovitzer , Jiacheng Weng , and Arash Arami , Member , IEEE

The estimator is finally tested on a participant walking with an active exoskeleton, demonstrating the robustness of D67 in interaction with an exoskeleton without being trained on any data from the test subject with or without an exoskeleton.

Interaction-Aware Planning With Deep Inverse Reinforcement Learning for Human-Like Autonomous Driving in Merge Scenarios

1 code implementation • journal 2023 • Jiangfeng Nan , Weiwen Deng , Member , IEEE , Ruzheng Zhang , Ying Wang , Rui Zhao , Juan Ding

To consider the interaction factor, the reward function for planning is utilized to evaluate the joint trajectories of the autonomous driving vehicle (ADV) and traffic vehicles.

Spoof Trace Disentanglement for generic face antispoofing

no code implementations • journal 2023 • Yaojie Liu and Xiaoming Liu , Member , IEEE

Yet, it is a challenging task due to the diversity of spoof attacks and the lack of ground truth for spoof traces.

Bio-Inspired Feature Selection in Brain Disease Detection via an Improved Sparrow Search Algorithm

no code implementations • IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022 • Wenyu Yu , Hui Kang , Geng Sun , Member , Shuang Liang , and Jiahui Li , Student Member , IEEE

Finally, the proposed ISSA is utilized to solve the objective function.

VCI-LSTM: Vector Choquet Integral-based Long Short-Term Memory

no code implementations • IEEE 2022 • Mikel Ferrero-Jaurrieta , Zdenko Taka ́cˇ , Javier Ferna ́ndez , Member , IEEE , Lˇubom ́ıra Horanska ́ , Grac ̧aliz Pereira Dimuro , Susana Montes , Irene D ́ıaz and Humberto Bustince , Fellow , IEEE.

Choquet integral is a widely used aggregation oper- ator on one-dimensional and interval-valued information, since it is able to take into account the possible interaction among data.

Lightweight Deep Neural Network for Joint Learning of Underwater Object Detection and Color Conversion

no code implementations • journal 2022 • Chia-Hung Yeh , Chu-Han Lin , Li-Wei Kang , Member , Chih-Hsiang Huang , Min-Hui Lin , Chuan-Yu Chang , and Chua-Chin Wang , Senior Member , IEEE

Li-Wei Kang is with the Department of Electrical Engineering, National Taiwan Normal University, Taipei 106, Taiwan (e-mail: lwkang@ntnu. edu. tw).

Topology Change Aware Data-Driven Probabilistic Distribution State Estimation Based on Gaussian Process

no code implementations • IEEE Transactions on Smart Grid 2022 • Di Cao , Member , Junbo Zhao , Weihao Hu , Senior Member , Qishu Liao , Qi Huang , Zhe Chen , Fellow , IEEE

Abstract—This paper addresses the distribution system state estimation (DSSE) with unknown topology change.

STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network

no code implementations • IEEE Transactions on Industrial Informatics 2022 • Ryan Wen Liu , Maohan Liang , Jiangtian Nie , Yanli Yuan , Zehui Xiong , Member , IEEE , Han Yu

—The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT).

Coverage Control Algorithm for DSNs Based on Improved Gravitational Search

no code implementations • IEEE Sensors Journal 2022 • Yindi Yao , Huanmin Liao , Xiong Li , Student Member , IEEE , Feng Zhao , Xuan Yang , and Shanshan Hu

—In directional sensor networks (DSNs), coverage control is an important way to ensure efficient communication and reliable data transmission.

High-order Correlation Preserved Incomplete Multi-view Subspace Clustering

3 code implementations • IEEE Transactions on Image Processing 2022 • Zhenglai Li , Chang Tang , Xiao Zheng , Xinwang Liu , Senior Member , Wei zhang , Member , IEEE , and En Zhu

Specifically, multiple affinity matrices constructed from the incomplete multi-view data are treated as a thirdorder low rank tensor with a tensor factorization regularization which preserves the high-order view correlation and sample correlation.

A GAN-Based Short-Term Link Traffic Prediction Approach for Urban Road Networks Under a Parallel Learning Framework

no code implementations • IEEE Transactions on Intelligent Transportation Systems 2022 • Junchen Jin , Member , IEEE , Dingding Rong , Tong Zhang , Qingyuan Ji , Haifeng Guo , Yisheng Lv , Xiaoliang Ma , and Fei-Yue Wang

This paper proposes a short-term traffic speed prediction approach, called PL-WGAN, for urban road networks, which is considered an important part of a novel parallel learning framework for traffic control and operation.

Shallow Network Based on Depthwise Over-Parameterized Convolution for Hyperspectral Image Classification

no code implementations • 1 Dec 2021 • Hongmin Gao , Member , Zhonghao Chen , Student Member , IEEE , Chenming Li

Therefore, this letter proposes a shallow model for HSIC, which is called depthwise over-parameterized convolutional neural network (DOCNN).

Distributed Differential Evolution Based on Adaptive Mergence and Split for Large-Scale Optimization

1 code implementation • IEEE Transactions on Evolutionary Computation 2021 • Yinglan Feng , Liang Feng , Senior Member , Sam Kwong , and Kay Chen Tan , Fellow , IEEE

In this way, the number of subpopulations is adaptively adjusted and better performing subpopulations obtain more individuals.

Double Deep Q-learning Based Real-Time Optimization Strategy for Microgrids

no code implementations • 27 Jul 2021 • Hang Shuai , Xiaomeng Ai , Jiakun Fang , Wei Yao , Senior Member , Jinyu Wen , Member , IEEE

It is challenging to solve this kind of stochastic nonlinear optimization problem.

A Novel Deep Learning Method for Thermal to Annotated Thermal-Optical Fused Images

no code implementations • 13 Jul 2021 • Suranjan Goswami , IEEE Student Member , Satish Kumar Singh , Senior Member , Bidyut B. Chaudhuri , Life Fellow , IEEE

As a part of this work, we also present a new and unique database for obtaining the region of interest in thermal images based on an existing thermal visual paired database, containing the Region of Interest on 5 different classes of data.

Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving

no code implementations • IEEE Transactions on Intelligent Transportation Systems 2021 • Liangtian Wan , Yuchen Sun , Lu Sun , Member , Zhaolong Ning , Senior Member , and Joel J. P. C. Rodrigues , Fellow , IEEE

Abstract— In this paper, a novel system architecture including a massive multi-input multi-output (MIMO) or a reconfigurable intelligent surface (RIS) and multiple autonomous vehicles is considered in vehicle location systems.

Content-Preserving Image Stitching with Piecewise Rectangular Boundary Constraints

no code implementations • IEEE Transactions on Visualization and Computer Graphics 2021 • Yun Zhang , Yu-Kun Lai , and Fang-Lue Zhang , Member , IEEE

By analyzing the irregular boundary, we construct a piecewise rectangular boundary.

Deep Reinforcement Learning Based Optimization for IRS Based UAV-NOMA Downlink Networks

no code implementations • 17 Jun 2021 • Shiyu Jiao , Ximing Xie , Zhiguo Ding , Fellow , IEEE

This paper investigates the application of deep deterministic policy gradient (DDPG) to intelligent reflecting surface (IRS) based unmanned aerial vehicles (UAV) assisted non-orthogonal multiple access (NOMA) downlink networks.

Detailed Primary and Secondary Distribution System Model Enhancement Using AMI Data

no code implementations • 29 May 2021 • Karen Montano-Martinez , Sushrut Thakar , Shanshan Ma , Zahra Soltani , Student Member , Vijay Vittal , Life Fellow , Mojdeh Khorsand , Raja Ayyanar , Senior Member , Cynthia Rojas , Member , IEEE

Reliable and accurate distribution system modeling, including the secondary network, is essential in examining distribution system performance with high penetration of distributed energy resources (DERs).

Context-aware taxi dispatching at city-scale using deep reinforcement learning

no code implementations • IEEE Transactions on Intelligent Transportation Systems 2021 • Zhidan Liu , Jiangzhou Li , and Kaishun Wu , Member , IEEE

Abstract— Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among different locations in a city.

Low-Complexity Symbol Detection and Interference Cancellation for OTFS System

no code implementations • 期刊 2021 • Huiyang Qu , Guanghui Liu , Lei Zhang , Shan Wen , Graduate Student Member , and Muhammad Ali Imran , Senior Member , IEEE

Orthogonal time frequency space (OTFS) is a two-dimensional modulation scheme realized in the delay- Doppler domain, which targets the robust wireless transmissions in high-mobility environments.

Multi-Scale and Multi-Direction GAN for CNN-Based Single Palm-V ein Identification

no code implementations • IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2021 • Huafeng Qin , Mounim A. El-Y acoubi , Y a n t a o L i , Member , IEEE , and Chongwen Liu

Despite recent advances of deep neural networks in hand vein identification, the existing solutions assume the availability of a large and rich set of training image samples.

Joint Trajectory and Power Allocation Design for Secure Artificial Noise Aided UAV Communications

no code implementations • journals 2021 • Milad Tatar Mamaghani , Graduate Student Member , and Yi Hong , Senior Member , IEEE

This paper investigates an average secrecy rate (ASR) maximization problem for an unmanned aerial vehicle (UAV) enabled wireless communication system, wherein a UAV is employed to deliver confidential information to a ground destination in the presence of a terrestrial passive eavesdropper.

Data-Driven Assisted Chance-Constrained Energy and Reserve Scheduling with Wind Curtailment

no code implementations • 2 Nov 2020 • Xingyu Lei , Student Member , Zhifang Yang , Member , Junbo Zhao , Juan Yu , Senior Member , IEEE

Case studies performed on the PJM 5-bus and IEEE 118-bus systems demonstrate that the proposed method is capable of accurately accounting the influence of wind curtailment dispatch in CCO.

Systems and Control Systems and Control

CRPN-SFNet: A High-Performance Object Detector on Large-Scale Remote Sensing Images

no code implementations • 28 Oct 2020 • QiFeng Lin , Jianhui Zhao , Gang Fu , and Zhiyong Yuan , Member , IEEE

Extensive experiments on the public Dataset for Object deTection in Aerial images data set indicate that our CRPN can help our detector deal the larger image faster with the limited GPU memory; meanwhile, the SFNet is beneficial to achieve more accurate detection of geospatial objects with wide-scale range.

Frame-wise Cross-modal Matching for Video Moment Retrieval

1 code implementation • 22 Sep 2020 • Haoyu Tang , Jihua Zhu , Meng Liu , Member , IEEE , Zan Gao , Zhiyong Cheng

Another contribution is that we propose an additional predictor to utilize the internal frames in the model training to improve the localization accuracy.

Attention Transfer Network for Nature Image Matting

1 code implementation • IEEE Transactions on Circuits and Systems for Video Technology 2020 • Fenfen Zhou , Yingjie Tian , Member , IEEE , and Zhiquan Qi

Then, we introduce a scale transfer block to magnify the feature maps without adding extra information.

A New Multiple Source Domain Adaptation Fault Diagnosis Method between Different Rotating Machines

no code implementations • TRANSACTIONS ON INDUSTRIAL INFORMA TICS 2020 • un Zhu , Nan Chen , Member , IEEE , and Changqing Shen

To solve this issue, transfer learning is proposed by leveraging knowl- edge learned from source domain to target domain.

Learning Person Re-identification Models from Videos with Weak Supervision

no code implementations • 21 Jul 2020 • Xueping Wang , Sujoy Paul , Dripta S. Raychaudhuri , Min Liu , Yaonan Wang , Amit K. Roy-Chowdhury , Fellow , IEEE

In order to cope with this issue, we introduce the problem of learning person re-identification models from videos with weak supervision.

Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach

no code implementations • IEEE Transactions on Industrial Informatics 2020 • Ameer Hamza Khan , Student Member , Shuai Li , and Xin Luo , Senior Member , IEEE

In this article, we present a metaheuristic-based control framework, called beetle antennae olfactory recurrent neural network, for simultaneous tracking control and obstacle avoidance of a redundant manipulator.

Edge server deployment scheme of blockchain in IoVs

no code implementations • 16 Jun 2020 • Liya Xu , Mingzhu Ge , Weili Wu , Member , IEEE

In fact, the application of blockchain in IoVs can be implemented by employing edge computing.

Service Provisioning Framework for RAN Slicing: User Admissibility, Slice Association and Bandwidth Allocation

no code implementations • IEEE Transactions on Mobile Computing 2020 • Yao Sun , Shuang Qin , Member , Gang Feng , Lei Zhang , and Muhammad Ali Imran , SeniorMember , IEEE

Network slicing (NS) has been identified as one of the most promising architectural technologies for future mobile network systems to meet the extremely diversified service requirements of users.

A Simplified 2D-3D CNN Architecture for Hyperspectral Image Classification Based on Spatial–Spectral Fusion

no code implementations • 5 Jun 2020 • Chunyan Yu , Rui Han , Meiping Song , Caiyu Liu , and Chein-I Chang , Life Fellow , IEEE

Abstract—Convolutional neural networks (CNN) have led to a successful breakthrough for hyperspectral image classification (HSIC).

Decision Fusion in Space-Time Spreading aided Distributed MIMO WSNs

no code implementations • 16 May 2020 • I. Dey , H. Joshi , Member , N. Marchetti , Senior Member , IEEE

In this letter, we propose space-time spreading (STS) of local sensor decisions before reporting them over a wireless multiple access channel (MAC), in order to achieve flexible balance between diversity and multiplexing gain as well as eliminate any chance of intrinsic interference inherent in MAC scenarios.

Energy-Efficient Over-the-Air Computation Scheme for Densely Deployed IoT Networks

no code implementations • IEEE 2020 • Semiha Tedik Basaran , Student Member , Gunes Karabulut Kurt , and Periklis Chatzimisios , Senior Member , IEEE

The proposed MMSE estimator provides a signif- icant mean squared error improvement with reducing en- ergy consumption compared to the conventional estimator.

A Lightweight and Privacy-Preserving Authentication Protocol for Mobile Edge Computing

no code implementations • 27 Feb 2020 • Kuljeet Kaur∗ , Sahil Garg∗ , Georges Kaddoum∗ , Member , Mohsen Guizani† , Fellow , IEEE , and Dushantha Nalin K. Jayakody‡ , Senior Member , IEEE.

With the advent of the Internet-of-Things (IoT), vehicular networks and cyber-physical systems, the need for realtime data processing and analysis has emerged as an essential pre-requite for customers’ satisfaction.

Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning

1 code implementation • 24 Feb 2020 • Chongwen Huang , Member , IEEE , Ronghong Mo , Chau Yuen , Senior Member

In this paper, we investigate the joint design of transmit beamforming matrix at the base station and the phase shift matrix at the RIS, by leveraging recent advances in deep reinforcement learning (DRL).

Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model

no code implementations • TRANSACTION 2020 • Yazhou Hu , Wenxue Wang , Hao liu , and Lianqing Liu , Member , IEEE

In this algorithm, a reward function is defined according to the features of tracking control in order to speed up the learning process, and then an RL tracking controller with a kernel-based transition dynamic model is proposed.

Broad Learning System Based on Maximum Correntropy Criterion

no code implementations • 24 Dec 2019 • Yunfei Zheng , Badong Chen , Shiyuan Wang , Senior Member , Weiqun Wang , Member , IEEE

As an effective and efficient discriminative learning method, Broad Learning System (BLS) has received increasing attention due to its outstanding performance in various regression and classification problems.

Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications

no code implementations • IEEE Internet of Things Journal 2019 • Muhammad Yeasir Arafat , Sangman Moh , Member , IEEE

Second, we propose an energy-efficient swarm-intelligence-based clustering (SIC) algorithm based on PSO, in which the particle fitness function is exploited for inter-cluster distance, intra-cluster distance, residual energy, and geographic location.

GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection

1 code implementation • 5 May 2019 • Qi. Wang , Senior Member , Zhenghang Yuan , Qian Du , Xuelong. Li , Fellow , IEEE

In order to better handle high dimension problem and explore abundance information, this paper presents a General End-to-end Two-dimensional CNN (GETNET) framework for hyperspectral image change detection (HSI-CD).

VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection

no code implementations • 5 May 2019 • Yuan Yuan , Zhitong Xiong , Student Member , Qi. Wang , Senior Member , IEEE

Our contributions are as follows: 1) We propose a multi-resolution feature fusion network architecture which exploits densely connected deconvolution layers with skip connections, and can learn more effective features for the small size object; 2) We frame the traffic sign detection as a spatial sequence classification and regression task, and propose a vertical spatial sequence attention (VSSA) module to gain more context information for better detection performance.

Discrete-Time Impulsive Adaptive Dynamic Programming

no code implementations • IEEE Transactions on Cybernetics 2019 • Qinglai Wei , Ruizhuo Song , Member , IEEE , Zehua Liao , Benkai Li , and Frank L. Lewis

Abstract—In this paper, a new iterative adaptive dynamic programming (ADP) algorithm is developed to solve optimal impulsive control problems for infinite horizon discrete-time nonlinear systems.

Generalization of the Dark Channel Prior for Single Image Restoration

no code implementations • IEEE Transactions on Image Processing 2019 • Yan-Tsung Peng , Keming Cao , and Pamela C. Cosman , Fellow , IEEE

Abstract— Images degraded by light scattering and absorption, such as hazy, sandstorm, and underwater images, often suffer color distortion and low contrast because of light traveling through turbid media.

A MIP Model for Risk Constrained Switch Placement in Distribution Networks

no code implementations • IEEE 2019 • Milad Izadi , Student Member , IEEE and Amir Safdarian , Member , IEEE

The model is applied to the RBTS-Bus4 and a real distribution network.

PEA265: Perceptual Assessment of Video Compression Artifacts

no code implementations • 1 Mar 2019 • Liqun Lin , Shiqi Yu , Tiesong Zhao , Member , Zhou Wang , Fellow , IEEE

To monitor and improve visual QoE, it is crucial to develop subjective and objective measures that can identify and quantify various types of PEAs.

A Provably Secure and Efficient Identity-Based Anonymous Authentication Scheme for Mobile Edge Computing

no code implementations • 22 Feb 2019 • Xiaoying Jia，Debiao He , Neeraj Kumar , and Kim-Kwang Raymond Choo , Senior Member , IEEE

Mobile edge computing (MEC) allows one to overcome a number of limitations inherent in cloud computing, although achieving the broad range of security requirements in MEC settings remains challenging.

Location-Centered House Price Prediction: A Multi-Task Learning Approach

no code implementations • 7 Jan 2019 • Guangliang Gao , Zhifeng Bao , Jie Cao , A. K. Qin , Timos Sellis , Fellow , IEEE , Zhiang Wu

Regarding the choice of prediction model, we observe that a variety of approaches either consider the entire house data for modeling, or split the entire data and model each partition independently.

DATS: Dispersive Stable Task Scheduling in Heterogeneous Fog Networks

no code implementations • Conference 2018 • Zening Liu , Xiumei Yang , Yang Yang , Kunlun Wang , and Guoqiang Mao , Fellow , IEEE

Abstract—Fog computing has risen as a promising architecture for future Internet of Things (IoT), 5G and embedded artificial intelligence (AI) applications with stringent service delay requirements along the cloud to things continuum.

Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks

no code implementations • IEEE INTERNET OF THINGS JOURNAL, VOL. 6, NO. 3 2018 • Jiawen Kang , Rong Y u , Xumin Huang , Maoqiang Wu , Sabita Maharjan , Member , Shengli Xie , and Y an Zhang , Senior Member , IEEE

Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i. e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources.

Optimal Training for Residual Self-Interference for Full-Duplex One-Way Relays

no code implementations • 13 Aug 2018 • Xiaofeng Li , Cihan Tepedelenlio˘glu , and Habib ¸Senol , Member , IEEE

For the former, we propose a training scheme to estimate the overall channel, and for the latter the CRB and the optimal number of relays are derived when the distance between the source and the destination is fixed.

Medical Image Synthesis with Deep Convolutional Adversarial Networks

1 code implementation • IEEE Transactions on Biomedical Engineering 2018 • Dong Nie , Roger Trullo , Jun Lian , Li Wang , Caroline Petitjean , Su Ruan , Qian Wang , and Dinggang Shen , Fellow , IEEE

To better model a nonlinear mapping from source to target and to produce more realistic target images, we propose to use the adversarial learning strategy to better model the FCN.

Single Image Dehazing Using Color Ellipsoid Prior

1 code implementation • IEEE Transactions on Image Processing 2018 • Trung Minh Bui , Student Member , and Wonha Kim , Senior Member , IEEE

The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry.

Significantly Fast and Robust Fuzzy C-MeansClustering Algorithm Based on MorphologicalReconstruction and Membership Filtering

no code implementations • IEEE 2018 • Tao Lei , Xiaohong Jia , Yanning Zhang , Lifeng He , Hongy-ing Meng , Senior Member , and Asoke K. Nandi , Fellow , IEEE

However, the introduction oflocal spatial information often leads to a high computationalcomplexity, arising out of an iterative calculation of the distancebetween pixels within local spatial neighbors and clusteringcenters.

An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing

no code implementations • 8 Dec 2017 • Dimitrios S. Alexiadis , Anargyros Chatzitofis , Nikolaos Zioulis , Olga Zoidi , Georgios Louizis , Dimitrios Zarpalas , Petros Daras , Senior Member , IEEE

The latest developments in 3D capturing, processing, and rendering provide means to unlock novel 3D application pathways.

Robust Single Image Super-Resolution via Deep Networks With Sparse Prior

1 code implementation • journals 2016 • Ding Liu , Zhaowen Wang , Bihan Wen , Student Member , Jianchao Yang , Member , Wei Han , and Thomas S. Huang , Fellow , IEEE

We demonstrate that a sparse coding model particularly designed for SR can be incarnated as a neural network with the merit of end-to-end optimization over training data.

A Decentralized Cooperative Control Scheme With Obstacle Avoidance for a Team of Mobile Robots

no code implementations • journal 2013 • Hamed Rezaee , Student Member , and Farzaneh Abdollahi , Member , IEEE

The problem of formation control of a team of mobile robots based on the virtual and behavioral structures is considered in this paper.

A Grid-Based Evolutionary Algorithm for Many-Objective Optimization

1 code implementation • IEEE Transactions on Evolutionary Computation 2013 • Shengxiang Yang , Member , IEEE , Miqing Li , Xiaohui Liu , and Jinhua Zheng

Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO).

Physiological Parameter Monitoring from Optical Recordings with a Mobile Phone

no code implementations • 29 Jul 2011 • Christopher G. Scully , Student Member , Jinseok Lee , Joseph Meyer , Alexander M. Gorbach , Domhnull Granquist-Fraser , Yitzhak Mendelson , Member , and Ki H. Chon , Senior Member , IEEE

We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor.

Performance Analysis of Two Hop Amplify-and-Forward Systems with Interference at the Relay

no code implementations • journal 2010 • Himal A. Suraweera , Member , HariK.Garg , and A. Nallanathan , Senior Member , IEEE

Abstract—We analyze the performance of a two hop channel state information (CSI)-assisted amplify-and-forward system, with co-channel interference at the relay.

Efficiently Indexing Large Sparse Graphs for Similarity Search

no code implementations • 18 Feb 2010 • Guoren Wang , Bin Wang , Xiaochun Yang , IEEE Computer Society , and Ge Yu , Member , IEEE

Abstract—The graph structure is a very important means to model schemaless data with complicated structures, such as protein- protein interaction networks, chemical compounds, knowledge query inferring systems, and road networks.

ANALYSIS OF CALIBRATED SEA CLUTTER AND BOAT REFLECTIVITY DATA AT C- AND X-BAND IN SOUTH AFRICAN COASTAL WATERS

no code implementations • IEEE 2007 • Ron Rubinstein , Member , Tomer Peleg , Student Member , and Michael Elad , Fellow , IEEE

Abstract—The synthesis-based sparse representation model for signals has drawn considerable interest in the past decade.

Parameter-free Geometric Document Layout Analysis

no code implementations • IEEE Transactions on Pattern Analysis and Machine Intelligence 2001 • Seong-Whan Lee , Senior Member , IEEE , and Dae-Seok Ryu

Based on the proposed periodicity measure, multiscale analysis, and confirmation procedure, we could develop a robust method for geometric document layout analysis independent of character font sizes, text line spacing, and document layout structures.

This year's conference is dedicated to the memory of Prof. Lotfi Zadeh , Honorary Chair and Prof. Thouraya Bouabana-Tebibel . Both Thouraya and Lotfi were among the warmest of personalities. They will be missed, but not forgotten. Professor Lotfi Zadeh was a frequent keynote speaker at IRI conferences. He showed us how reuse was an inherently fuzzy concept – setting the stage for knowledge acquisition. He taught us that when someone insults you, you take it as a compliment. Moreover, Professor Zadeh entwined a sense of humor, hard work, and good science with a sense of adventure. Fuzzy numbers were extensions of logic. Computing with words was an extension of speech. He held that nothing is worth doing unless you believed in it; and, if you don’t believe in yourself, the outside world will not believe in your words either. Professor Zadeh will be missed; albeit, he will be by our side in death as in life. Professor Thouraya Bouabana-Tebibel ran the conferences formal workshop for many years. She was a kind soul, an ardent researcher, and an excellent educator. She published many conference papers and pursued formal approaches to data science. Professor Tebibel will be remembered for her tireless efforts, her many students, and her pursuit of AI through reuse and randomization. The conference cannot be the same without her; but, her teachings surely put us all on the road to success. Professor Tebibel was a great woman, a role model, and a source of inspiration for us all. She will be sadly missed. Read More

Keynote Speakers

Some New Data Challenges in Data Science

Huan liu professor.

“Chameleons” – Actors Who Can “Play Any Part”: Your Data Can Have a Starring Role Too!

Matthew c. stafford chief learning officer.

Graph Neural Networks for Supporting Knowledge-Data Integrated Machine Learning

Aidong zhang william wulf faculty fellow and professor of computer science, important dates, about ieee iri.

IEEE BigData 2016

IEEE BigData 2024 Washington DC, USA

Special Symposium

Special symposium 1:, special symposium 2:, undergraduate and high school symposium, 2024 national symposium for nsf reu research in data science, systems, and security (reu 2024 symposium).

Description Undergraduate research plays an important role in attracting our best undergraduates to continue towards graduate education in the science and engineering fields. Publishing research in a professional venue is part of the training for future researchers. The National Science Foundation (NSF) provides support for undergraduate research within the Research Experience for Undergraduates (REU) program. The goal of this Symposium is to provide a venue for students to publish their research done as part of the REU program. The symposium seeks original submissions in research areas that are currently funded by the NSF's directorate for Computer and Information Science and Engineering (CISE) or other related directorates. The research topics of this symposium focus on Data Science, Systems, and Security. Research done by undergraduate researchers without explicit funding sources or via funding from similar programs such as Louis Stokes Alliances for Minority Participation (LSAMP) are also eligible to submit. The key requirement for this Symposium is that the submission's lead author must be an undergraduate student or high school student. To promote research experiences in K-12, high school students are also eligible to submit although it is highly recommended such submissions are in collaboration with undergraduate students and/or faculty mentors. The same REU Symposium has been held in 2021, 2022 and 2023. More information can be found at REU Symposium 2021 , REU Symposium 2022 , REU Symposium 2023 . The same REU Symposium has been held in Big Data 2019 ( https://bigdataieee.org/BigData2019/SpecialSymposium.html ), Big Data 2018 ( https://bigdataieee.org/BigData2018/SpecialSymposium.html ), and Big Data 2021 ( https://bigdataieee.org/BigData2021/SpecialSymposium.html ).

• Paper submission due date: Tuesday, September 5, 2024
• Decision notification: September 25, 2024
• Camera-ready due date: October 5, 2024
• Pre-registration: October 15, 2024
• Symposium: One day in December 15-18, 2024

Paper Submission Authors are invited to submit full papers (maximal 10 pages) or short papers (maximal 6 pages) as per IEEE 8.5 x 11 manuscript guidelines (templates for LaTex, Word and PDF can be found at IEEE Templates for Conference Proceedings ). All papers must be submitted via the conference submission system for the symposium . At least one author of each accepted paper is required to attend the symposium and present the paper. All the accepted papers by the symposium will be included in the Proceedings of the IEEE Big Data 2024 Conference (IEEE BigData 2024) which will be published by IEEE Computer Society.

• Dr. Xuechen Zhang , Washington State University, Organizer of the NSF REU Site on Advancing Data-Driven Deep Coupling of Computational Simulations and Experiments
• Dr. Xiaokun Yang , University of Houston-Clear Lake, Co-Organizer of the NSF REU Site on Advancing Data-Driven Deep Coupling of Computational Simulations and Experiments
• Dr. Xinghui Zhao , Washington State University, Co-Organizer of the NSF REU Site on Advancing Data-Driven Deep Coupling of Computational Simulations and Experiments
• Dr. Matthias K. Gobbert , University of Maryland, Baltimore County, Organizer of the NSF REU Site on Online Interdisciplinary Big Data Analytics in Science and Engineering
• Dr. Jianwu Wang , University of Maryland, Baltimore County, Co-Organizer of the NSF REU Site on Online Interdisciplinary Big Data Analytics in Science and Engineering