Check computer science papers: citations, claims and retractions

Training deep neural networks with low precision multiplications

Courbariaux, M., Bengio, Y., & David, J.-P. (2014) · arXiv

Numerical Methods and AlgorithmsAdvanced Neural Network Applications

Cited by 407

DenseBox: Unifying Landmark Localization with End to End Object Detection

Huang, L., Yang, Y., Deng, Y., & Yu, Y. (2015) · arXiv

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 407

Virtual memory

Denning, P. J. (1970) · ACM Computing Surveys

Parallel Computing and Optimization TechniquesLogic, programming, and type systems

Cited by 407

Out-of-Distribution Generalization via Risk Extrapolation (REx)

Krueger, D., Caballero, E., Jacobsen, J.-H., Zhang, A., Binas, J., Zhang, D., Priol, R. L., & Courville, A. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 407

Why We Need New Evaluation Metrics for NLG

Novikova, J., Dušek, O., Curry, A. C., & Rieser, V. (2017) · arXiv

Natural Language Processing TechniquesSpeech and dialogue systems

Cited by 406

Quantum error-correcting codes associated with graphs

Schlingemann, D., & Werner, R. F. (2001) · Physical Review A

Quantum Computing Algorithms and ArchitectureCoding theory and cryptography

Cited by 406

From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality

Ying, Z., Niu, H., Gupta, P., Mahajan, D., Ghadiyaram, D., & Bovik, A. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Image and Video Quality AssessmentDigital Media Forensic Detection

Cited by 406

Mask R-CNN

He, K., Gkioxari, G., Dollár, P., & Girshick, R. (2017) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 406

A Comparison of MCC and CEN Error Measures in Multi-Class Prediction

Jurman, G., Riccadonna, S., & Furlanello, C. (2012) · PLoS ONE

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 406

PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

Tang, P., Wang, X., Bai, S., Shen, W., Bai, X., Liu, W., & Yuille, A. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 406

ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning

Gu, Q., Kuwajerwala, A., Morin, S., Jatavallabhula, K. M., Sen, B., Agarwal, A., Rivera, C., Paul, W., Ellis, K., Chellappa, R., et al. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

3D Shape Modeling and AnalysisRobot Manipulation and Learning

Cited by 406

Super‐resolution musculoskeletal MRI using deep learning

Chaudhari, A. S., Fang, Z., Kogan, F., Wood, J., Stevens, K. J., Gibbons, E. K., Lee, J. H., Gold, G. E., & Hargreaves, B. A. (2018) · Magnetic Resonance in Medicine

Advanced Image Processing TechniquesAdvanced MRI Techniques and Applications

Cited by 406

Attack of the tails: Yes, you really can backdoor federated learning

Wang, H., Sreenivasan, K., Rajput, S., Vishwakarma, H., Agarwal, S., Sohn, J.-Y., Lee, K., & Papailiopoulos, D. (2020) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 406

The Use and Abuse of Cell Phones and Text Messaging in the Classroom: A Survey of College Students

Tindell, D. R., & Bohlander, R. W. (2012) · College Teaching

Mobile Learning in EducationImpact of Technology on Adolescents

Cited by 406

Zero Trust Architecture (ZTA): A Comprehensive Survey

Syed, N. F., Shah, S. W., Shaghaghi, A., Anwar, A., Baig, Z., & Doss, R. (2022) · IEEE Access

Access Control and TrustInformation and Cyber Security

Cited by 406

Benchmarking deep learning models on large healthcare datasets

Purushotham, S., Meng, C., Che, Z., & Liu, Y. (2018) · Journal of Biomedical Informatics

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 406

Time series shapelets: a novel technique that allows accurate, interpretable and fast classification

Ye, L., & Keogh, E. (2011) · Data Mining and Knowledge Discovery

Time Series Analysis and ForecastingImage Retrieval and Classification Techniques

Cited by 406

Blockchain as a confidence machine: The problem of trust & challenges of governance

De Filippi, P., Mannan, M., & Reijers, W. (2020) · Technology in Society

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 406

Online Multi-object Tracking Using CNN-Based Single Object Tracker with Spatial-Temporal Attention Mechanism

Chu, Q., Ouyang, W., Li, H., Wang, X., Liu, B., & Yu, N. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 406

Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry

Köbis, N., & Mossink, L. D. (2021) · Computers in Human Behavior

Ethics and Social Impacts of AINatural Language Processing Techniques

Cited by 406

Logic for Equivocators

Lewis, D. (1982) · Noûs

Logic, Reasoning, and KnowledgeAdvanced Algebra and Logic

Cited by 406

Quality and productivity outcomes relating to continuous integration in GitHub

Vasilescu, B., Yu, Y., Wang, H., Devanbu, P., & Filkov, V. (2015) · Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering

Software Engineering Techniques and PracticesSoftware Engineering Research

Cited by 406

Measuring the Quality of Explanations: The System Causability Scale (SCS): Comparing Human and Machine Explanations

Holzinger, A., Carrington, A., & Müller, H. (2020) · KI - Künstliche Intelligenz

Explainable Artificial Intelligence (XAI)Usability and User Interface Design

Cited by 406

Knowledge Graph and Text Jointly Embedding

Wang, Z., Zhang, J., Feng, J., & Chen, Z. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingAdvanced Graph Neural Networks

Cited by 406