Check computer science papers: citations, claims and retractions

A hybrid latent space data fusion method for multimodal emotion recognition

Nemati, S., Rohani, R., Basiri, M. E., Abdar, M., Yen, N. Y., & Makarenkov, V. (2019) · IEEE Access

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 98

The Self-Perception and Political Biases of ChatGPT

Rutinowski, J., Franke, S., Endendyk, J., Dormuth, I., Roidl, M., & Pauly, M. (2024) · Human Behavior and Emerging Technologies

Ethics and Social Impacts of AISocial Media and Politics

Cited by 98

Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis

Tsai, Y.-H. H., Ma, M., Yang, M., Salakhutdinov, R., & Morency, L.-P. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Multimodal Machine Learning ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 98

GAN-generated Faces Detection: A Survey and New Perspectives

Wang, X., Guo, H., Hu, S., Chang, M.-C., & Lyu, S. (2022) · arXiv

Digital Media Forensic DetectionFace recognition and analysis

Cited by 98

Meta Reinforcement Learning for Sim-to-real Domain Adaptation

Arndt, K., Hazara, M., Ghadirzadeh, A., & Kyrki, V. (2019) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 98

Disease Prediction via Graph Neural Networks

Sun, Z., Yin, H., Chen, H., Chen, T., Cui, L., & Yang, F. (2021) · IEEE Journal of Biomedical and Health Informatics

Machine Learning in HealthcareAdvanced Graph Neural Networks

Cited by 98

Emotions as discrete patterns of systemic activity

Nummenmaa, L., & Saarimäki, H. (2019) · Neuroscience Letters

Emotion and Mood RecognitionNeural and Behavioral Psychology Studies

Cited by 98

Warning: Humans cannot reliably detect speech deepfakes

Mai, K. T., Bray, S., Davies, T., & Griffin, L. D. (2023) · PLOS ONE

Speech Recognition and SynthesisDigital Media Forensic Detection

Cited by 98

Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks

Nam, W.-J., Gur, S., Choi, J., Wolf, L., & Lee, S.-W. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 98

An End-to-End Architecture for Class-Incremental Object Detection with Knowledge Distillation

Hao, Y., Fu, Y., Jiang, Y.-G., & Tian, Q. (2019) · 2019 IEEE International Conference on Multimedia and Expo (ICME)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 98

Detection of Cyberbullying Using Deep Neural Network

Banerjee, V., Telavane, J., Gaikwad, P., & Vartak, P. (2019) · 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)

Hate Speech and Cyberbullying DetectionSpam and Phishing Detection

Cited by 98

Low cost crowd counting using audio tones

Kannan, P. G., Venkatagiri, S. P., Chan, M. C., Ananda, A. L., & Peh, L.-S. (2012) · Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems

Mobile Crowdsensing and CrowdsourcingIndoor and Outdoor Localization Technologies

Cited by 97

Energy compaction-based image compression using convolutional autoencoder

Cheng, Z., Sun, H., Takeuchi, M., & Katto, J. (2020) · IEEE Transactions on Multimedia

Advanced Data Compression TechniquesVideo Coding and Compression Technologies

Cited by 97

Mop moiré patterns using mopnet

He, B., Wang, C., Shi, B., & Duan, L. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Image Processing TechniquesImage Enhancement Techniques

Cited by 97

CitySense: blockchain-oriented smart cities

Ibba, S., Pinna, A., Seu, M., & Pani, F. E. (2017) · Proceedings of the XP2017 Scientific Workshops

Blockchain Technology Applications and SecuritySmart Cities and Technologies

Cited by 97

Breast cancer diagnosis using support vector machine optimized by improved quantum inspired grey wolf optimization

Bilal, A., Imran, A., Baig, T. I., Liu, X., Abouel Nasr, E., & Long, H. (2024) · Scientific Reports

AI in cancer detectionMetaheuristic Optimization Algorithms Research

Cited by 97

When Confidence Meets Accuracy: Exploring the Effects of Multiple Performance Indicators on Trust in Machine Learning Models

Rechkemmer, A., & Yin, M. (2022) · CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Human-Automation Interaction and Safety

Cited by 97

Suing the algorithm: the mundanization of automated decision-making in public services through litigation

Kaun, A. (2022) · Information, Communication & Society

Ethics and Social Impacts of AIE-Government and Public Services

Cited by 97

ARCANE: An Efficient Architecture for Exact Machine Unlearning

Yan, H., Li, X., Guo, Z., Li, H., Li, F., & Lin, X. (2022) · Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 97

Notice of Removal: Multiresolution Knowledge Distillation for Anomaly Detection

Salehi, M., Sadjadi, N., Baselizadeh, S., Rohban, M. H., & Rabiee, H. R. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Anomaly Detection Techniques and ApplicationsAdversarial Robustness in Machine Learning

Cited by 97

Direct answers for search queries in the long tail

Bernstein, M. S., Teevan, J., Dumais, S., Liebling, D., & Horvitz, E. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Information Retrieval and Search BehaviorExpert finding and Q&A systems

Cited by 97

The Threat of Offensive AI to Organizations

Mirsky, Y., Demontis, A., Kotak, J., Shankar, R., Gelei, D., Yang, L., Zhang, X., Pintor, M., Lee, W., Elovici, Y., et al. (2023) · Computers & Security

Adversarial Robustness in Machine LearningInformation and Cyber Security

Cited by 97

Reducing hallucination in structured outputs via Retrieval-Augmented Generation

Ayala, O., & Bechard, P. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track)

Topic ModelingNatural Language Processing Techniques

Cited by 97

Accelerating Sparse Deep Neural Networks

Mishra, A., Latorre, J. A., Pool, J., Stosic, D., Stosic, D., Venkatesh, G., Yu, C., & Micikevicius, P. (2021) · arXiv

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 97