Check computer science papers: citations, claims and retractions

One-Shot Video Object Segmentation

Caelles, S., Maninis, K.-K., Pont-Tuset, J., Leal-Taixe, L., Cremers, D., & Van Gool, L. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 927

Healthcare blockchain system using smart contracts for secure automated remote patient monitoring

Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Hayajneh, T. (2018) · Journal of Medical Systems

Blockchain Technology Applications and SecurityInternet of Things and AI

Cited by 926

Training deep networks for facial expression recognition with crowd-sourced label distribution

Barsoum, E., Zhang, C., Ferrer, C. C., & Zhang, Z. (2016) · Proceedings of the 18th ACM International Conference on Multimodal Interaction

Emotion and Mood RecognitionMachine Learning and Data Classification

Cited by 926

The CIPIC HRTF database

Algazi, V. R., Duda, R. O., Thompson, D. M., & Avendano, C. (2002) · Proceedings of the 2001 IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics (Cat. No.01TH8575)

Speech and Audio ProcessingHuman auditory perception and evaluation

Cited by 926

CoAtNet: Marrying Convolution and Attention for All Data Sizes

Dai, Z., Liu, H., Le, Q. V., & Tan, M. (2021) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 925

Questioning the AI: Informing Design Practices for Explainable AI User Experiences

Liao, Q. V., Gruen, D., & Miller, S. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Usability and User Interface Design

Cited by 925

Sparsity Invariant CNNs

Uhrig, J., Schneider, N., Schneider, L., Franke, U., Brox, T., & Geiger, A. (2017) · 2017 International Conference on 3D Vision (3DV)

Advanced Neural Network ApplicationsAdvanced Vision and Imaging

Cited by 924

A review of emotion recognition using physiological signals

Shu, L., Xie, J., Yang, M., Li, Z., Li, Z., Liao, D., Xu, X., & Yang, X. (2018) · Sensors

Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control

Cited by 923

A Survey on Neural Network Interpretability

Zhang, Y., Tino, P., Leonardis, A., & Tang, K. (2021) · IEEE Transactions on Emerging Topics in Computational Intelligence

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 923

A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network

Nguyen, D. Q., Nguyen, T. D., Nguyen, D. Q., & Phung, D. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)

Advanced Graph Neural NetworksTopic Modeling

Cited by 923

Active Learning for Convolutional Neural Networks: A Core-Set Approach

Sener, O., & Savarese, S. (2017) · arXiv

Machine Learning and AlgorithmsDomain Adaptation and Few-Shot Learning

Cited by 922

Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing

Dellaert, F., & Kaess, M. (2006) · The International Journal of Robotics Research

Robotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor Networks

Cited by 922

A whole-slide foundation model for digital pathology from real-world data

Xu, H., Usuyama, N., Bagga, J., Zhang, S., Rao, R., Naumann, T., Wong, C., Gero, Z., González, J., Gu, Y., et al. (2024) · Nature

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 921

Learning when training data are costly: the effect of class distribution on tree induction

Weiss, G. M., & Provost, F. (2003) · Journal of Artificial Intelligence Research

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 921

Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere

Wang, T., & Isola, P. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 921

Machine learning for internet of things data analysis: a survey

Mahdavinejad, M. S., Rezvan, M., Barekatain, M., Adibi, P., Barnaghi, P., & Sheth, A. P. (2018) · Digital Communications and Networks

Internet of Things and AIIoT and Edge/Fog Computing

Cited by 921

A survey of convergence results on particle filtering methods for practitioners

Crisan, D., & Doucet, A. (2002) · IEEE Transactions on Signal Processing

Target Tracking and Data Fusion in Sensor NetworksMarkov Chains and Monte Carlo Methods

Cited by 919

ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing

Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023) · Journal of the Association for Information Science and Technology

Ethics and Social Impacts of AIAcademic integrity and plagiarism

Cited by 919

Can blockchain strengthen the internet of things?

Kshetri, N. (2017) · IT Professional

Blockchain Technology Applications and SecurityInternet of Things and AI

Cited by 918

The ethics of artificial intelligence

Bostrom, N., & Yudkowsky, E. (2014) · The Cambridge Handbook of Artificial Intelligence

Ethics and Social Impacts of AILiterary and Philosophical Studies

Cited by 918

Envisioning AI for K-12: What Should Every Child Know about AI?

Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Teaching and Learning ProgrammingArtificial Intelligence in Education

Cited by 918

Guide to Attribute Based Access Control (ABAC) Definition and Considerations

Hu, V. C., Ferraiolo, D., Kuhn, R., Schnitzer, A., Sandlin, K., Miller, R., & Scarfone, K. (2014)

Access Control and TrustInformation and Cyber Security

Cited by 917

Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism

Li, Y., Zeng, J., Shan, S., & Chen, X. (2019) · IEEE Transactions on Image Processing

Emotion and Mood RecognitionFace recognition and analysis

Cited by 916

A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos

Schops, T., Schonberger, J. L., Galliani, S., Sattler, T., Schindler, K., Pollefeys, M., & Geiger, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Vision and Imaging3D Surveying and Cultural Heritage

Cited by 915