Check computer science papers: citations, claims and retractions

Judging Perceived and Traversed Distance in Virtual Environments

Witmer, B. G., & Kline, P. B. (1998) · Presence: Teleoperators and Virtual Environments

Virtual Reality Applications and ImpactsSpatial Cognition and Navigation

Cited by 335

CopyCatch: stopping group attacks by spotting lockstep behavior in social networks

Beutel, A., Xu, W., Guruswami, V., Palow, C., & Faloutsos, C. (2013) · Proceedings of the 22nd international conference on World Wide Web

Spam and Phishing DetectionComplex Network Analysis Techniques

Cited by 335

Application of Blockchain and Internet of Things in Healthcare and Medical Sector: Applications, Challenges, and Future Perspectives

Ratta, P., Kaur, A., Sharma, S., Shabaz, M., & Dhiman, G. (2021) · Journal of Food Quality

Blockchain Technology Applications and SecurityInternet of Things and AI

Cited by 335

Deep Structured Energy Based Models for Anomaly Detection

Zhai, S., Cheng, Y., Lu, W., & Zhang, Z. (2016) · arXiv

Anomaly Detection Techniques and ApplicationsAdversarial Robustness in Machine Learning

Cited by 334

Artificial intelligence, transparency, and public decision-making: Why explanations are key when trying to produce perceived legitimacy

de Fine Licht, K., & de Fine Licht, J. (2020) · AI & SOCIETY

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 334

A Short Note on the Kinetics-700-2020 Human Action Dataset

Smaira, L., Carreira, J., Noland, E., Clancy, E., Wu, A., & Zisserman, A. (2020) · arXiv

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 334

Targeted Syntactic Evaluation of Language Models

Marvin, R., & Linzen, T. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesSyntax, Semantics, Linguistic Variation

Cited by 334

Robust single-view geometry and motion reconstruction

Li, H., Adams, B., Guibas, L. J., & Pauly, M. (2009) · ACM Transactions on Graphics

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 334

Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images

Khosravi, P., Kazemi, E., Imielinski, M., Elemento, O., & Hajirasouliha, I. (2018) · EBioMedicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 334

Multimodal Convolutional Neural Networks for Matching Image and Sentence

Ma, L., Lu, Z., Shang, L., & Li, H. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 334

Local Relation Learning for Face Forgery Detection

Chen, S., Yao, T., Chen, Y., Ding, S., Li, J., & Ji, R. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence

Digital Media Forensic DetectionFace recognition and analysis

Cited by 334

Multiple feature hashing for real-time large scale near-duplicate video retrieval

Song, J., Yang, Y., Huang, Z., Shen, H. T., & Hong, R. (2011) · Proceedings of the 19th ACM international conference on Multimedia

Advanced Image and Video Retrieval TechniquesVideo Analysis and Summarization

Cited by 334

Is Pseudo-Lidar needed for Monocular 3D Object detection?

Park, D., Ambrus, R., Guizilini, V., Li, J., & Gaidon, A. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Vision and Imaging

Cited by 334

A Survey on Automated Log Analysis for Reliability Engineering

He, S., He, P., Chen, Z., Yang, T., Su, Y., & Lyu, M. R. (2022) · ACM Computing Surveys

Software System Performance and ReliabilitySoftware Reliability and Analysis Research

Cited by 334

WoodScape: A Multi-Task, Multi-Camera Fisheye Dataset for Autonomous Driving

Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Chennupati, S., Uricar, M., Milz, S., Simon, M., Amende, K., Witt, C., et al. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Vision and Imaging

Cited by 334

Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining

Hajian, S., Bonchi, F., & Castillo, C. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Ethics and Social Impacts of AIPrivacy-Preserving Technologies in Data

Cited by 334

Shepherding the crowd yields better work

Dow, S., Kulkarni, A., Klemmer, S., & Hartmann, B. (2012) · Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work

Mobile Crowdsensing and CrowdsourcingExpert finding and Q&A systems

Cited by 334

Outlier Detection: Methods, Models, and Classification

Boukerche, A., Zheng, L., & Alfandi, O. (2021) · ACM Computing Surveys

Anomaly Detection Techniques and ApplicationsAdvanced Statistical Methods and Models

Cited by 334

The future of quantum computing with superconducting qubits

Bravyi, S., Dial, O., Gambetta, J. M., Gil, D., & Nazario, Z. (2022) · Journal of Applied Physics

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 334

Multimodal sentiment analysis with word-level fusion and reinforcement learning

Chen, M., Wang, S., Liang, P. P., Baltrušaitis, T., Zadeh, A., & Morency, L.-P. (2017) · Proceedings of the 19th ACM International Conference on Multimodal Interaction

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 334

InnoHAR: A Deep Neural Network for Complex Human Activity Recognition

Xu, C., Chai, D., He, J., Zhang, X., & Duan, S. (2019) · IEEE Access

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 333

Time Series Classification with HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles

Lines, J., Taylor, S., & Bagnall, A. (2018) · ACM Transactions on Knowledge Discovery from Data

Time Series Analysis and ForecastingMusic and Audio Processing

Cited by 333

A New Deep Learning-Based Food Recognition System for Dietary Assessment on An Edge Computing Service Infrastructure

Liu, C., Cao, Y., Luo, Y., Chen, G., Vokkarane, V., Yunsheng, M., Chen, S., & Hou, P. (2018) · IEEE Transactions on Services Computing

IoT and Edge/Fog ComputingAdvanced Neural Network Applications

Cited by 333

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study

Sano, A., Taylor, S., McHill, A. W., Phillips, A. J., Barger, L. K., Klerman, E., & Picard, R. (2018) · Journal of Medical Internet Research

Emotion and Mood RecognitionDigital Mental Health Interventions

Cited by 333