Check computer science papers: citations, claims and retractions

Deep Learning and Explainable Artificial Intelligence Techniques Applied for Detecting Money Laundering–A Critical Review

Kute, D. V., Pradhan, B., Shukla, N., & Alamri, A. (2021) · IEEE Access

Imbalanced Data Classification TechniquesCrime, Illicit Activities, and Governance

Cited by 209

Uncertainty-Aware Score Distribution Learning for Action Quality Assessment

Tang, Y., Ni, Z., Zhou, J., Zhang, D., Lu, J., Wu, Y., & Zhou, J. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Human Pose and Action RecognitionImage and Video Quality Assessment

Cited by 209

Surveillance Capitalism or Democracy? The Death Match of Institutional Orders and the Politics of Knowledge in Our Information Civilization

Zuboff, S. (2022) · Organization Theory

Ethics and Social Impacts of AICultural Studies and Postmodernism

Cited by 209

P-DBSCAN: a density based clustering algorithm for exploration and analysis of attractive areas using collections of geo-tagged photos

Kisilevich, S., Mansmann, F., & Keim, D. (2010) · Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application

Data Management and AlgorithmsAdvanced Clustering Algorithms Research

Cited by 209

Measuring Calibration in Deep Learning

Nixon, J., Dusenberry, M., Jerfel, G., Nguyen, T., Liu, J., Zhang, L., & Tran, D. (2019) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 209

Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance

Raji, I. D., Xu, P., Honigsberg, C., & Ho, D. (2022) · Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 209

Dual Contrastive Learning for General Face Forgery Detection

Sun, K., Yao, T., Chen, S., Ding, S., Li, J., & Ji, R. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence

Digital Media Forensic DetectionFace recognition and analysis

Cited by 209

A Comprehensive Review on Artificial Intelligence/Machine Learning Algorithms for Empowering the Future IoT Toward 6G Era

Mahmood, M. R., Matin, M. A., Sarigiannidis, P., & Goudos, S. K. (2022) · IEEE Access

Internet of Things and AIIoT and Edge/Fog Computing

Cited by 209

A survey on behavior analysis in video surveillance for homeland security applications

Ko, T. (2008) · 2008 37th IEEE Applied Imagery Pattern Recognition Workshop

Video Surveillance and Tracking MethodsHuman Pose and Action Recognition

Cited by 209

Vocal and Facial Biomarkers of Depression based on Motor Incoordination and Timing

Williamson, J. R., Quatieri, T. F., Helfer, B. S., Ciccarelli, G., & Mehta, D. D. (2014) · Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 209

Wearable sensors for Parkinson’s disease: which data are worth collecting for training symptom detection models

Lonini, L., Dai, A., Shawen, N., Simuni, T., Poon, C., Shimanovich, L., Daeschler, M., Ghaffari, R., Rogers, J. A., & Jayaraman, A. (2018) · npj Digital Medicine

Context-Aware Activity Recognition SystemsNon-Invasive Vital Sign Monitoring

Cited by 209

Score-Based Point Cloud Denoising

Luo, S., & Hu, W. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

3D Shape Modeling and AnalysisImage and Signal Denoising Methods

Cited by 209

Auditing Partisan Audience Bias within Google Search

Robertson, R. E., Jiang, S., Joseph, K., Friedland, L., Lazer, D., & Wilson, C. (2018) · Proceedings of the ACM on Human-Computer Interaction

Information Retrieval and Search BehaviorSocial Media and Politics

Cited by 209

When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning

Wang, S., Tuor, T., Salonidis, T., Leung, K. K., Makaya, C., He, T., & Chan, K. (2018) · IEEE INFOCOM 2018 - IEEE Conference on Computer Communications

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 209

Demonstration of Fidelity Improvement Using Dynamical Decoupling with Superconducting Qubits

Pokharel, B., Anand, N., Fortman, B., & Lidar, D. A. (2018) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 209

On-line policy improvement using Monte-Carlo search

Tesauro, G., & Galperin, G. R. (2025) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 209

Integration of acoustic and visual speech signals using neural networks

Yuhas, B. P., Goldstein, M. H., & Sejnowski, T. J. (1989) · IEEE Communications Magazine

Speech and Audio ProcessingSpeech Recognition and Synthesis

Cited by 209

The Role of Virtual Reality in Improving Health Outcomes for Community-Dwelling Older Adults: Systematic Review

Dermody, G., Whitehead, L., Wilson, G., & Glass, C. (2020) · Journal of Medical Internet Research

Virtual Reality Applications and ImpactsTechnology Use by Older Adults

Cited by 209

Calibration of Pre-trained Transformers

Desai, S., & Durrett, G. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 209

Data preprocessing in predictive data mining

Alexandropoulos, S.-A. N., Kotsiantis, S. B., & Vrahatis, M. N. (2019) · The Knowledge Engineering Review

Machine Learning and Data ClassificationData Mining and Machine Learning Applications

Cited by 209

Discriminative Reconstruction Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection

Jiang, T., Li, Y., Xie, W., & Du, Q. (2020) · IEEE Transactions on Geoscience and Remote Sensing

Remote-Sensing Image ClassificationAnomaly Detection Techniques and Applications

Cited by 209

Paper prototyping - what is it good for?: a comparison of paper- and computer-based low-fidelity prototyping

Sefelin, R., Tscheligi, M., & Giller, V. (2003) · CHI '03 extended abstracts on Human factors in computing systems - CHI '03

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 209

Proceedings of the 25th International Conference on Intelligent User Interfaces

(2020)

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 209

How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees

Colledanchise, M., & Ogren, P. (2017) · IEEE Transactions on Robotics

AI-based Problem Solving and PlanningArtificial Intelligence in Games

Cited by 209