Check computer science papers: citations, claims and retractions

Context Based Emotion Recognition Using EMOTIC Dataset

Kosti, R., Alvarez, J., Recasens, A., & Lapedriza, A. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Emotion and Mood RecognitionFace recognition and analysis

Cited by 211

Learning analytics in higher education --- challenges and policies: a review of eight learning analytics policies

Tsai, Y.-S., & Gasevic, D. (2017) · Proceedings of the Seventh International Learning Analytics & Knowledge Conference

Online Learning and AnalyticsBig Data and Business Intelligence

Cited by 211

AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

Zhong, W., Cui, R., Guo, Y., Liang, Y., Lu, S., Wang, Y., Saied, A., Chen, W., & Duan, N. (2024) · Findings of the Association for Computational Linguistics: NAACL 2024

Topic ModelingArtificial Intelligence Applications

Cited by 211

Progressing to the Center: Coordinating Project Work

Dahlander, L., & O'Mahony, S. (2011) · Organization Science

Open Source Software InnovationsTeam Dynamics and Performance

Cited by 211

Multimodal 2D+3D Facial Expression Recognition With Deep Fusion Convolutional Neural Network

Li, H., Sun, J., Xu, Z., & Chen, L. (2017) · IEEE Transactions on Multimedia

Face recognition and analysisEmotion and Mood Recognition

Cited by 211

Automated rationale generation: a technique for explainable AI and its effects on human perceptions

Ehsan, U., Tambwekar, P., Chan, L., Harrison, B., & Riedl, M. O. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)AI-based Problem Solving and Planning

Cited by 210

The need for multivocal literature reviews in software engineering: complementing systematic literature reviews with grey literature

Garousi, V., Felderer, M., & Mäntylä, M. V. (2016) · Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering

Software Engineering Techniques and PracticesMeta-analysis and systematic reviews

Cited by 210

AI agents under threat: A survey of key security challenges and future pathways

Deng, Z., Guo, Y., Han, C., Ma, W., Xiong, J., Wen, S., & Xiang, Y. (2025) · ACM Computing Surveys

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 210

Human-centered XAI: Developing design patterns for explanations of clinical decision support systems

Schoonderwoerd, T. A. J., Jorritsma, W., Neerincx, M. A., & van den Bosch, K. (2021) · International Journal of Human-Computer Studies

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 210

Self-Supervised Spatio-Temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics

Wang, J., Jiao, J., Bao, L., He, S., Liu, Y., & Liu, W. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Human Pose and Action RecognitionDomain Adaptation and Few-Shot Learning

Cited by 210

The Cambridge Handbook of Information and Computer Ethics

(2010) · Cambridge University Press eBooks

Ethics and Social Impacts of AIInformation Society and Technology Trends

Cited by 210

Optimizing Variational Quantum Algorithms Using Pontryagin’s Minimum Principle

Yang, Z.-C., Rahmani, A., Shabani, A., Neven, H., & Chamon, C. (2017) · Physical Review X

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 210

Causality in thought

Sloman, S. A., & Lagnado, D. (2015) · Annual Review of Psychology

Bayesian Modeling and Causal InferenceLogic, Reasoning, and Knowledge

Cited by 210

Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace

Kollias, D., & Zafeiriou, S. (2019) · arXiv

Emotion and Mood RecognitionFace recognition and analysis

Cited by 210

A Deep Learning Model to Triage Screening Mammograms: A Simulation Study

Yala, A., Schuster, T., Miles, R., Barzilay, R., & Lehman, C. (2019) · Radiology

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 210

From Log Files to Assessment Metrics: Measuring Students' Science Inquiry Skills Using Educational Data Mining

Gobert, J. D., Sao Pedro, M., Raziuddin, J., & Baker, R. S. (2013) · Journal of the Learning Sciences

Intelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics

Cited by 210

Building Ethics into Artificial Intelligence

Yu, H., Shen, Z., Miao, C., Leung, C., Lesser, V. R., & Yang, Q. (2018) · Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence

Ethics and Social Impacts of AIEthics in Business and Education

Cited by 210

Graph Echo State Networks

Gallicchio, C., & Micheli, A. (2010) · The 2010 International Joint Conference on Neural Networks (IJCNN)

Neural Networks and Reservoir ComputingNeural Networks and Applications

Cited by 210

GSum: A General Framework for Guided Neural Abstractive Summarization

Dou, Z.-Y., Liu, P., Hayashi, H., Jiang, Z., & Neubig, G. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingAdvanced Text Analysis Techniques

Cited by 210

FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows

Yu, J., Zheng, Y., Wang, X., Li, W., Wu, Y., Zhao, R., & Wu, L. (2021) · arXiv

Anomaly Detection Techniques and ApplicationsIndustrial Vision Systems and Defect Detection

Cited by 210

A handle bar metaphor for virtual object manipulation with mid-air interaction

Song, P., Goh, W. B., Hutama, W., Fu, C.-W., & Liu, X. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Interactive and Immersive DisplaysHand Gesture Recognition Systems

Cited by 210

An expert system for brain tumor detection: Fuzzy C-means with super resolution and convolutional neural network with extreme learning machine

Özyurt, F., Sert, E., & Avcı, D. (2020) · Medical Hypotheses

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 210

End-to-End Race Driving with Deep Reinforcement Learning

Jaritz, M., de Charette, R., Toromanoff, M., Perot, E., & Nashashibi, F. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsAutonomous Vehicle Technology and Safety

Cited by 210

Comparison of Markerless and Marker-Based Motion Capture Technologies through Simultaneous Data Collection during Gait: Proof of Concept

Ceseracciu, E., Sawacha, Z., & Cobelli, C. (2014) · PLoS ONE

Human Motion and AnimationLower Extremity Biomechanics and Pathologies

Cited by 210