OOIR: Observatory of International Research

Papers

(The TQCC of IEEE Signal Processing Magazine is 6. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)

Article	Citations
Federated Learning: Challenges, Methods, and Future Directions	2094
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing	508
Lidar for Autonomous Driving: The Principles, Challenges, and Trends for Automotive Lidar and Perception Systems	294
MIMO Radar for Advanced Driver-Assistance Systems and Autonomous Driving: Advantages and Challenges	288
Joint Radar-Communication Strategies for Autonomous Vehicles: Combining Two Key Automotive Technologies	236
Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications	165
Snapshot Compressive Imaging: Theory, Algorithms, and Applications	163
Event-Based Neuromorphic Vision for Autonomous Driving: A Paradigm Shift for Bio-Inspired Visual Sensing and Perception	146
3D Point Cloud Processing and Learning for Autonomous Driving: Impacting Map Creation, Localization, and Perception	106
Self-Supervised Representation Learning: Introduction, advances, and challenges	104
Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques	92
Distributed Gradient Methods for Convex Machine Learning Problems in Networks: Distributed Optimization	85
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks	83
Graph Signal Processing for Machine Learning: A Review and New Perspectives	79
Sampling Signals on Graphs: From Theory to Applications	79
Sound Event Detection: A tutorial	76
Decentralized Stochastic Optimization and Machine Learning: A Unified Variance-Reduction Framework for Robust Performance and Fast Convergence	73
Radar Interference Mitigation for Automated Driving: Exploring Proactive Strategies	71
The Bussgang Decomposition of Nonlinear Systems: Basic Theory and MIMO Extensions [Lecture Notes]	68
Advances in Single-Photon Lidar for Autonomous Vehicles: Working Principles, Challenges, and Recent Advances	68
Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows	65
Rethinking Bayesian Learning for Data Analysis: The art of prior and inference in sparsity-aware modeling	63
Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning	56
Emotion Recognition From Multiple Modalities: Fundamentals and methodologies	56
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications	56

Present and Future of Reconfigurable Intelligent Surface-Empowered Communications [Perspectives]	54
Electroencephalography-Based Auditory Attention Decoding: Toward Neurosteered Hearing Devices	53
Federated Learning: A signal processing perspective	53
Artificial Intelligence Internet of Things for the Elderly: From Assisted Living to Health-Care Monitoring	49
Adversary-Resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model	48
Optimization for Reinforcement Learning: From a single agent to cooperative agents	48
A Physics-Informed Neural Network for Quantifying the Microstructural Properties of Polycrystalline Nickel Using Ultrasound Data: A promising approach for solving inverse problems	44
Two Applications of Deep Learning in the Physical Layer of Communication Systems [Lecture Notes]	43
Optimization and Learning With Information Streams: Time-varying algorithms and applications	43
Music Emotion Recognition: Toward new, robust standards in personalized and context-sensitive applications	40
Deep Inverse Reinforcement Learning for Behavior Prediction in Autonomous Driving: Accurate Forecasts of Vehicle Motion	40
Toward Open-World Electroencephalogram Decoding Via Deep Learning: A comprehensive survey	40
Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances	39
Personalized Education in the Artificial Intelligence Era: What to Expect Next	39
Noninvasive Neural Interfacing With Wearable Muscle Sensors: Combining Convolutive Blind Source Separation Methods and Deep Learning Techniques for Neural Decoding	38
Distributed Learning in the Nonconvex World: From batch data to streaming and beyond	38
Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology	35
Facial-Video-Based Physiological Signal Measurement: Recent advances and affective applications	34
Robust Explainability: A tutorial on gradient-based attribution methods for deep neural networks	33
Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective	31
Localized Spectral Graph Filter Frames: A Unifying Framework, Survey of Design Considerations, and Numerical Comparison	31
Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging: Theory, algorithms, and applications	31
Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement: An overview from a signal processing perspective	31
Signal Processing on Directed Graphs: The Role of Edge Directionality When Processing and Learning From Network Data	29
An Overview of the MPEG-5 Essential Video Coding Standard [Standards in a Nutshell]	28
A User Guide to Low-Pass Graph Signal Processing and Its Applications: Tools and Applications	26
The Global Landscape of Neural Networks: An Overview	26
Toward Robust Sensing for Autonomous Vehicles: An Adversarial Perspective	26
Deep Learning in Neuroimaging: Promises and challenges	26
Straggler-Resistant Distributed Matrix Computation via Coding Theory: Removing a Bottleneck in Large-Scale Data Processing	25
Human Machine Interfaces in Upper-Limb Prosthesis Control: A Survey of Techniques for Preprocessing and Processing of Biosignals	25
More Real Than Real: A Study on Human Visual Perception of Synthetic Faces [Applications Corner]	22
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing	22
Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning: Examining Distributed and Centralized Stochastic Gradient Descent	22
The Cramér–Rao Bound for Signal Parameter Estimation From Quantized Data [Lecture Notes]	22
Submodularity in Action: From Machine Learning to Signal Processing Applications	21
Signal Processing and Machine Learning Techniques for Terahertz Sensing: An overview	20
Twenty-Five Years of Advances in Beamforming: From convex and nonconvex optimization to learning techniques	20
Internet-of-Things Devices and Assistive Technologies for Health Care: Applications, Challenges, and Opportunities	20
Radio Map Estimation: A data-driven approach to spectrum cartography	19
Integrating the Role of Computational Intelligence and Digital Signal Processing in Education: Emerging Technologies and Mathematical Tools	19
Physics-Driven Synthetic Data Learning for Biomedical Magnetic Resonance: The imaging physics-based data synthesis paradigm for artificial intelligence	19
Novel Arithmetics in Deep Neural Networks Signal Processing for Autonomous Driving: Challenges and Opportunities	19
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition: A comparison of current training strategies	19
Seventy Years of Radar and Communications: The road from separation to integration	18
Understanding Notions of Stationarity in Nonsmooth Optimization: A Guided Tour of Various Constructions of Subdifferential for Nonsmooth Functions	18
Deep Learning for Mobile Mental Health: Challenges and recent advances	17
Physics-Inspired Compressive Sensing: Beyond deep unrolling	17
Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing: A summary of current methods	17
Topological Signal Processing: Making Sense of Data Building on Multiway Relations	16

Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]	16
Real-Time Interactive 4D-STEM Phase-Contrast Imaging From Electron Event Representation Data: Less computation with the right representation	16
Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness	15
Deep Representation Learning for Affective Speech Signal Analysis and Processing: Preventing unwanted signal disparities	15
Augmented/Mixed Reality Audio for Hearables: Sensing, control, and rendering	15
Multiway Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries	15
Interactive Learning of Signal Processing Through Music: Making Fourier Analysis Concrete for Students	15
Diagnosis/Prognosis of COVID-19 Chest Images via Machine Learning and Hypersignal Processing: Challenges, opportunities, and applications	14
Teaching Differently: The Digital Signal Processing of Multimedia Content Through the Use of Liberal Arts	14
Phase Retrieval: From Computational Imaging to Machine Learning: A tutorial	14
Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms	14
Machine Learning From Distributed, Streaming Data [From the Guest Editors]	12
Machine Learning for the Control of Prosthetic Arms: Using Electromyographic Signals for Improved Performance	12
Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging	12
Explainable Artificial Intelligence for Magnetic Resonance Imaging Aging Brainprints: Grounds and challenges	12
Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey	12
Deep Optical Coding Design in Computational Imaging: A data-driven framework	12
Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing: Nonlocal sparse and low-rank modeling	12
Improvements to the Sliding Discrete Fourier Transform Algorithm [Tips & Tricks]	11
The Hitchhiker’s Guide to Bias and Fairness in Facial Affective Signal Processing: Overview and techniques	11
Deep Unrolled Recovery in Sparse Biological Imaging: Achieving fast, accurate results	11
Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective	11
Integrated Sensing and Communications With Reconfigurable Intelligent Surfaces: From signal modeling to processing	11
Reconfigurable Intelligent Surface-Assisted Massive MIMO: Favorable propagation, channel hardening, and rank deficiency [Lecture Notes]	11
Physics-Embedded Machine Learning for Electromagnetic Data Imaging: Examining three types of data-driven imaging methods	11
Free Energy Minimization: A Unified Framework for Modeling, Inference, Learning, and Optimization [Lecture Notes]	10
An Efficient Algorithm for Maneuvering Target Tracking [Tips & Tricks]	10
Discriminative and Generative Learning for the Linear Estimation of Random Signals [Lecture Notes]	10
Integrating Psychometrics and Computing Perspectives on Bias and Fairness in Affective Computing: A case study of automated video interviews	10
Neural Target Speech Extraction: An overview	10
Explaining Artificial Intelligence Generation and Creativity: Human interpretability for novel ideas and artifacts	10
Self-Supervised Learning for Autonomous Vehicles Perception: A Conciliation Between Analytical and Learning Methods	10
Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications	10
Communications and Sensing: An Opportunity for Automotive Systems [From the Editor]	9
Nonconvex Structured Phase Retrieval: A Focus on Provably Correct Approaches	9
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging	9
ℓ ₂ and ℓ ₁ Trend Filtering: A Kalman Filter Approach [Lecture Notes]	9
Sketching Data Sets for Large-Scale Learning: Keeping only what you need	9
Deep Neural Network Perception Models and Robust Autonomous Driving Systems: Practical Solutions for Mitigation and Improvement	9
Physics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion	8
On the Evolution of Speech Representations for Affective Computing: A brief history and critical overview	8
Distributed No-Regret Learning in Multiagent Systems: Challenges and Recent Developments	8
Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches	8
Twenty-Five Years of Sensor Array and Multichannel Signal Processing: A review of progress to date and potential research directions	7
Proper Definition and Handling of Dirac Delta Functions [Lecture Notes]	7
An Observer-Based Adaptive Fourier Analysis [Tips & Tricks]	7
Graph Signal Processing: History, development, impact, and outlook	7
Community-Aware Graph Signal Processing: Modularity Defines New Ways of Processing Graph Signals	6
Geometry, Manifolds, and Nonconvex Optimization: How Geometry Can Help Optimization	6
Light-Field Microscopy for the Optical Imaging of Neuronal Activity: When model-based methods meet data-driven approaches	6
Interpretability, Reproducibility, and Replicability [From the Guest Editors]	6
Signal Processing for Neurorehabilitation and Assistive Technologies [From the Guest Editors]	6
Signal Processing on Signed Graphs: Fundamentals and Potentials	6
A Survey of Artificial Intelligence in Fashion	6
Polynomial Eigenvalue Decomposition for Multichannel Broadband Signal Processing: A mathematical technique offering new insights and solutions	6
Rethinking Engineering Education: Policy, Pedagogy, and Assessment During Crises	6
Optimally Compressed Nonparametric Online Learning: Tradeoffs between memory and consistency	6
Blue-Noise Sampling of Graph and Multigraph Signals: Dithering on Non-Euclidean Domains	6
Simulating the Autonomous Future: A Look at Virtual Vehicle Environments and How to Validate Simulation Using Public Data Sets	6