Check computer science papers: citations, claims and retractions

Physical Security and Safety of IoT Equipment: A Survey of Recent Advances and Opportunities

Yang, X., Shu, L., Liu, Y., Hancke, G. P., Ferrag, M. A., & Huang, K. (2022) · IEEE Transactions on Industrial Informatics

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 93

Wireless distributed computing: a survey of research challenges

Datla, D., Chen, X., Tsou, T., Raghunandan, S., Hasan, S. M., Reed, J., Dietrich, C., Bose, T., Fette, B., & Kim, J.-H. (2012) · IEEE Communications Magazine

Cognitive Radio Networks and Spectrum SensingDistributed and Parallel Computing Systems

Cited by 93

Goals and Tasks: Two Typologies of Citizen Science Projects

Wiggins, A., & Crowston, K. (2012) · 2012 45th Hawaii International Conference on System Sciences

Open Source Software InnovationsMobile Crowdsensing and Crowdsourcing

Cited by 93

Creating a sustainable digital infrastructure: The role of service-oriented architecture

Hustad, E., & Olsen, D. H. (2021) · Procedia Computer Science

Service-Oriented Architecture and Web ServicesCloud Computing and Resource Management

Cited by 93

Noise Based Deepfake Detection via Multi-Head Relative-Interaction

Wang, T., & Chow, K. P. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 93

SPEED: An Inhabitant Activity Prediction Algorithm for Smart Homes

Alam, M. R., Reaz, M. B. I., & Mohd Ali, M. A. (2012) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans

Context-Aware Activity Recognition SystemsIoT-based Smart Home Systems

Cited by 93

Goal-directed control and its antipodes

Dayan, P. (2009) · Neural Networks

Reinforcement Learning in RoboticsNeural and Behavioral Psychology Studies

Cited by 93

CF-YOLO: Cross Fusion YOLO for Object Detection in Adverse Weather With a High-Quality Real Snow Dataset

Ding, Q., Li, P., Yan, X., Shi, D., Liang, L., Wang, W., Xie, H., Li, J., & Wei, M. (2023) · IEEE Transactions on Intelligent Transportation Systems

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 93

TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications

Chen, Z., Narayanan, N., Fang, B., Li, G., Pattabiraman, K., & DeBardeleben, N. (2020) · 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE)

Software Testing and Debugging TechniquesDistributed systems and fault tolerance

Cited by 93

Deep Neural Networks with Relativity Learning for facial expression recognition

Guo, Y., Tao, D., Yu, J., Xiong, H., Li, Y., & Tao, D. (2016) · 2016 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)

Emotion and Mood RecognitionFace recognition and analysis

Cited by 93

Finetuning Large Language Models for Vulnerability Detection

Shestov, A., Levichev, R., Mussabayev, R., Maslov, E., Cheshkov, A., & Zadorozhny, P. (2024) · arXiv

Software Engineering ResearchWeb Application Security Vulnerabilities

Cited by 93

Deep Neural Network based Human Activity Recognition for the Order Picking Process

Grzeszick, R., Lenk, J. M., Rueda, F. M., Fink, G. A., Feldhorst, S., & ten Hompel, M. (2017) · Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 93

Scaling Autoregressive Video Models

Weissenborn, D., Täckström, O., & Uszkoreit, J. (2019) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 93

Human Activity Recognition from Wearable Sensor Data Using Self-Attention

Saif, M., Tanjid Hasan Tonmoy, M., Kishor, K. B., Mahbubur Rahman, A. K. M., Ashraful Amin, M., Mohammad, S., Muhammad, A. H. K., & Amin, A. A. (2020) · Frontiers in Artificial Intelligence and Applications

Context-Aware Activity Recognition SystemsTime Series Analysis and Forecasting

Cited by 93

C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection

Tan, C., Tao, R., Liu, H., Gu, G., Wu, B., Zhao, Y., & Wei, Y. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 93

ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Zhang, D., Zhoubian, S., Hu, Z., Yue, Y., Dong, Y., & Tang, J. (2024) · Advances in Neural Information Processing Systems 37

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 93

A Review of Insider Threat Detection Approaches With IoT Perspective

Kim, A., Oh, J., Ryu, J., & Lee, K. (2020) · IEEE Access

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 93

Real-time visual tracking of 3d objects with dynamic handling of occlusion

Wunsch, P., & Hirzinger, G. (2002) · Proceedings of International Conference on Robotics and Automation

Advanced Vision and ImagingVideo Surveillance and Tracking Methods

Cited by 93

Attention is not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion

Liang, T., Lin, G., Feng, L., Zhang, Y., & Lv, F. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 93

OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web

Kapoor, R., Butala, Y. P., Russak, M., Koh, J. Y., Kamble, K., Alshikh, W., & Salakhutdinov, R. (2024) · arXiv

Multimodal Machine Learning ApplicationsSpeech and dialogue systems

Cited by 93

IOTFLA : A Secured and Privacy-Preserving Smart Home Architecture Implementing Federated Learning

Aivodji, U. M., Gambs, S., & Martin, A. (2019) · 2019 IEEE Security and Privacy Workshops (SPW)

Privacy-Preserving Technologies in DataIoT-based Smart Home Systems

Cited by 93

A Systematic Analysis of Accessibility in Computing Education Research

Baker, C. M., El-Glaly, Y. N., & Shinohara, K. (2020) · Proceedings of the 51st ACM Technical Symposium on Computer Science Education

Teaching and Learning ProgrammingDigital Accessibility for Disabilities

Cited by 93

The body beyond the body: expectation of a sensory event is enough to induce ownership over a fake hand

Ferri, F., Chiarelli, A. M., Merla, A., Gallese, V., & Costantini, M. (2013) · Proceedings of the Royal Society B: Biological Sciences

Virtual Reality Applications and ImpactsTactile and Sensory Interactions

Cited by 93

Pengembangan Multimedia Pembelajaran Interaktif Berpendekatan CTL Pada Pembelajaran Tematik Siswa Kelas IV SD

Geni, K. H. Y. W., Sudarma, I. K., & Mahadewi, L. P. P. (2020) · Jurnal Edutech Undiksha

Multimedia Learning SystemsEducational Technology and E-Learning

Cited by 93