Check computer science papers: citations, claims and retractions

DCR-net: a deep co-interactive relation network for joint dialog act recognition and sentiment classification

Qin, L., Che, W., Li, Y., Ni, M., & Liu, T. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Speech and dialogue systemsSentiment Analysis and Opinion Mining

Cited by 90

A survey of multimodal learning: Methods, applications, and future

Yuan, Y., Li, Z., & Zhao, B. (2025) · ACM Computing Surveys

Multimodal Machine Learning ApplicationsMultisensory perception and integration

Cited by 90

Adversarial Attacks Against Deep Generative Models on Data: A Survey

Sun, H., Zhu, T., Zhang, Z., Jin, D., Xiong, P., & Zhou, W. (2023) · IEEE Transactions on Knowledge and Data Engineering

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 90

Prediction, pre-emption and limits to dissent: Social media and big data uses for policing protests in the United Kingdom

Dencik, L., Hintz, A., & Carey, Z. (2018) · New Media & Society

Ethics and Social Impacts of AIPolicing Practices and Perceptions

Cited by 90

Segmentation and quantification of adipose tissue by magnetic resonance imaging

Hu, H. H., Chen, J., & Shen, W. (2016) · Magnetic Resonance Materials in Physics, Biology and Medicine

Medical Image Segmentation TechniquesAdvanced MRI Techniques and Applications

Cited by 90

Once a Kind Friend is Now a Thing: Understanding How Conversational Agents at Home are Forgotten

Cho, M., Lee, S.-S., & Lee, K.-P. (2019) · Proceedings of the 2019 on Designing Interactive Systems Conference

Innovative Human-Technology InteractionAI in Service Interactions

Cited by 90

Towards a Theory of Software Developer Job Satisfaction and Perceived Productivity

Storey, M.-A., Zimmermann, T., Bird, C., Czerwonka, J., Murphy, B., & Kalliamvakou, E. (2021) · IEEE Transactions on Software Engineering

Software Engineering Techniques and PracticesJob Satisfaction and Organizational Behavior

Cited by 90

μNAS: Constrained Neural Architecture Search for Microcontrollers

Liberis, E., Dudziak, Ł., & Lane, N. D. (2021) · Proceedings of the 1st Workshop on Machine Learning and Systems

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 90

Measure and Improve Robustness in NLP Models: A Survey

Wang, X., Wang, H., & Yang, D. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 90

Sample Subset Optimization Techniques for Imbalanced and Ensemble Learning Problems in Bioinformatics Applications

Yang, P., Yoo, P. D., Fernando, J., Zhou, B. B., Zhang, Z., & Zomaya, A. Y. (2014) · IEEE Transactions on Cybernetics

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 90

Driving SME innovation with AI solutions: overcoming adoption barriers and future growth opportunities

Iyelolu, T. V., Agu, E. E., Idemudia, C., & Ijomah, T. I. (2024) · International Journal of Science and Technology Research Archive

Artificial Intelligence ApplicationsImpact of AI and Big Data on Business and Society

Cited by 90

Employing fusion of learned and handcrafted features for unconstrained ear recognition

Hansley, E. E., Segundo, M. P., & Sarkar, S. (2018) · IET Biometrics

Biometric Identification and SecurityFace recognition and analysis

Cited by 90

Clova Baseline System for the VoxCeleb Speaker Recognition Challenge 2020

Heo, H. S., Lee, B.-J., Huh, J., & Chung, J. S. (2020) · arXiv

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 90

Probabilistic pointing target prediction via inverse optimal control

Ziebart, B., Dey, A., & Bagnell, J. A. (2012) · Proceedings of the 2012 ACM international conference on Intelligent User Interfaces

Interactive and Immersive DisplaysGaze Tracking and Assistive Technology

Cited by 90

Cryptanalysis and Improvement on an Image Encryption Algorithm Design Using a Novel Chaos Based S-Box

Zhu, C., Wang, G., & Sun, K. (2018) · Symmetry

Chaos-based Image/Signal EncryptionCryptographic Implementations and Security

Cited by 90

Towards Interpretable Face Recognition

Yin, B., Tran, L., Li, H., Shen, X., & Liu, X. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Face recognition and analysisFace and Expression Recognition

Cited by 90

Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale

Ramrakhya, R., Undersander, E., Batra, D., & Das, A. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 90

Auto-segmentation of pancreatic tumor in multi-parametric MRI using deep convolutional neural networks

Liang, Y., Schott, D., Zhang, Y., Wang, Z., Nasief, H., Paulson, E., Hall, W., Knechtges, P., Erickson, B., & Li, X. A. (2020) · Radiotherapy and Oncology

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 90

On The Computational Complexity of Self-Attention

Keles, F. D., Wijewardena, P. M., & Hegde, C. (2022) · arXiv

Complexity and Algorithms in GraphsTopic Modeling

Cited by 90

Combining policy gradient and Q-learning

O'Donoghue, B., Munos, R., Kavukcuoglu, K., & Mnih, V. (2016) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 90

Calibrated Language Models Must Hallucinate

Kalai, A. T., & Vempala, S. S. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 90

Dialogue Learning With Human-In-The-Loop

Li, J., Miller, A. H., Chopra, S., Ranzato, M., & Weston, J. (2016) · arXiv

Speech and dialogue systemsReinforcement Learning in Robotics

Cited by 90

Adaptive deep learning model selection on embedded systems

Taylor, B., Marco, V. S., Wolff, W., Elkhatib, Y., & Wang, Z. (2018) · Proceedings of the 19th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 90

Vision Transformers Need Registers

Darcet, T., Oquab, M., Mairal, J., & Bojanowski, P. (2023) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 90