Check computer science papers: citations, claims and retractions

After Innovation, Turn to Maintenance

Russell, A. L., & Vinsel, L. (2018) · Technology and Culture

History of Computing TechnologiesCybernetics and Technology in Society

Cited by 216

Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development

Scheuerman, M. K., Hanna, A., & Denton, R. (2021) · Proceedings of the ACM on Human-Computer Interaction

Ethics and Social Impacts of AIResearch Data Management Practices

Cited by 216

Identification of Anonymous MRI Research Participants with Face-Recognition Software

Schwarz, C. G., Kremers, W. K., Therneau, T. M., Sharp, R. R., Gunter, J. L., Vemuri, P., Arani, A., Spychalla, A. J., Kantarci, K., Knopman, D. S., et al. (2019) · New England Journal of Medicine

Face recognition and analysisFace Recognition and Perception

Cited by 215

Cloze-driven Pretraining of Self-attention Networks

Baevski, A., Edunov, S., Liu, Y., Zettlemoyer, L., & Auli, M. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 215

Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning

Chung, S., Lim, J., Noh, K. J., Kim, G., & Jeong, H. (2019) · Sensors

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 215

Multiple Object Tracking with Correlation Learning

Wang, Q., Zheng, Y., Pan, P., & Xu, Y. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 215

Separable Self-attention for Mobile Vision Transformers

Mehta, S., & Rastegari, M. (2022) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 215

Hierarchical active shape models, using the wavelet transform

Davatzikos, C., Tao, X., & Shen, D. (2003) · IEEE Transactions on Medical Imaging

Medical Image Segmentation Techniques3D Shape Modeling and Analysis

Cited by 215

Dangers and uses of cross-correlation in analyzing time series in perception, performance, movement, and neuroscience: The importance of constructing transfer function autoregressive models

Dean, R. T., & Dunsmuir, W. T. M. (2016) · Behavior Research Methods

Time Series Analysis and ForecastingComplex Systems and Time Series Analysis

Cited by 215

Monocular Relative Depth Perception with Web Stereo Data Supervision

Xian, K., Shen, C., Cao, Z., Lu, H., Xiao, Y., Li, R., & Luo, Z. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Vision and ImagingAdvanced Neural Network Applications

Cited by 215

Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI

Mueller, S. T., Hoffman, R. R., Clancey, W., Emrey, A., & Klein, G. (2019) · arXiv

Explainable Artificial Intelligence (XAI)Intelligent Tutoring Systems and Adaptive Learning

Cited by 215

Deep Fried Convnets

Yang, Z., Moczulski, M., Denil, M., De Freitas, N., Song, L., & Wang, Z. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsStochastic Gradient Optimization Techniques

Cited by 215

Acquisition of expanding targets

McGuffin, M., & Balakrishnan, R. (2002) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Interactive and Immersive DisplaysUsability and User Interface Design

Cited by 215

Open Science, Open Data, and Open Scholarship: European Policies to Make Science Fit for the Twenty-First Century

Burgelman, J.-C., Pascu, C., Szkuta, K., Von Schomberg, R., Karalopoulos, A., Repanas, K., & Schouppe, M. (2019) · Frontiers in Big Data

Research Data Management PracticesAcademic Publishing and Open Access

Cited by 215

An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation

Chu, C., Dabre, R., & Kurohashi, S. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Natural Language Processing TechniquesDomain Adaptation and Few-Shot Learning

Cited by 215

How good are detection proposals, really?

Hosang, J., Benenson, R., & Schiele, B. (2014) · Proceedings of the British Machine Vision Conference 2014

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 215

Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Domain Learning

Tan, C., Zhao, Y., Wei, S., Gu, G., Liu, P., & Wei, Y. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 215

Toward verified artificial intelligence

Seshia, S. A., Sadigh, D., & Sastry, S. S. (2022) · Communications of the ACM

Formal Methods in VerificationSafety Systems Engineering in Autonomy

Cited by 215

Operationalising AI Ethics: Barriers, Enablers and next Steps

Morley, J., Kinsey, L., Elhalal, A., Garcia, F., Ziosi, M., & Floridi, L. (2023) · AI & SOCIETY

Ethics and Social Impacts of AIEthics in Business and Education

Cited by 215

A Framework for Automatic Human Emotion Classification Using Emotion Profiles

Mower, E., Mataric, M. J., & Narayanan, S. (2011) · IEEE Transactions on Audio, Speech, and Language Processing

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 215

Training of quantum circuits on a hybrid quantum computer

Zhu, D., Linke, N. M., Benedetti, M., Landsman, K. A., Nguyen, N. H., Alderete, C. H., Perdomo-Ortiz, A., Korda, N., Garfoot, A., Brecque, C., et al. (2019) · Science Advances

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 215

Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms

Han, X., & Fischl, B. (2007) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 215

Statistics on diffeomorphisms via tangent space representations

Vaillant, M., Miller, M. I., Younes, L., & Trouvé, A. (2004) · NeuroImage

Medical Image Segmentation TechniquesTopological and Geometric Data Analysis

Cited by 215

Automated graph-based analysis and correction of cortical volume topology

Shattuck, D. W., & Leahy, R. M. (2001) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesDigital Image Processing Techniques

Cited by 215