Check computer science papers: citations, claims and retractions

A practical Bayesian framework for backpropagation networks

MacKay, D. J. C. (1992) · Neural Computation

Neural Networks and ApplicationsGaussian Processes and Bayesian Inference

Cited by 2,917

Segment anything in medical images

Ma, J., He, Y., Li, F., Han, L., You, C., & Wang, B. (2024) · Nature Communications

AI in cancer detectionMedical Image Segmentation Techniques

Cited by 2,913

Activity recognition using cell phone accelerometers

Kwapisz, J. R., Weiss, G. M., & Moore, S. A. (2011) · ACM SIGKDD Explorations Newsletter

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 2,912

Region-based convolutional networks for accurate object detection and segmentation

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 2,912

A Survey on Multi-Task Learning

Zhang, Y., & Yang, Q. (2017) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 2,910

Unsupervised Learning of Depth and Ego-Motion from Video

Zhou, T., Brown, M., Snavely, N., & Lowe, D. G. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Vision and ImagingRobotics and Sensor-Based Localization

Cited by 2,910

ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software

Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014) · PLoS ONE

Data Visualization and AnalyticsComplex Network Analysis Techniques

Cited by 2,909

Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials

Krähenbühl, P., & Koltun, V. (2012) · arXiv

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 2,908

RepVGG: Making VGG-style ConvNets Great Again

Ding, X., Zhang, X., Ma, N., Han, J., Ding, G., & Sun, J. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 2,907

Graph Theoretic Methods in Multiagent Networks

Mesbahi, M., & Egerstedt, M. (2010) · Princeton University Press eBooks

Distributed Control Multi-Agent SystemsNeural Networks Stability and Synchronization

Cited by 2,897

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

Sohn, K., Berthelot, D., Li, C.-L., Zhang, Z., Carlini, N., Cubuk, E. D., Kurakin, A., Zhang, H., & Raffel, C. (2020) · arXiv

Machine Learning and AlgorithmsDomain Adaptation and Few-Shot Learning

Cited by 2,892

An exploratory technique for investigating large quantities of categorical data

Kass, G. V. (1980) · Applied Statistics

Data Mining Algorithms and ApplicationsStatistical Methods and Applications

Cited by 2,880

How artificial intelligence will change the future of marketing

Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020) · Journal of the Academy of Marketing Science

AI in Service InteractionsArtificial Intelligence Applications

Cited by 2,875

Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning

Li, Q., Han, Z., & Wu, X.-M. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Advanced Graph Neural NetworksMachine Learning and Algorithms

Cited by 2,872

BERTScore: Evaluating Text Generation with BERT

Zhang, T., Kishore, V., Wu, F., Weinberger, K. Q., & Artzi, Y. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,865

Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture

Eigen, D., & Fergus, R. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Vision and Imaging

Cited by 2,862

Context Aware Computing for The Internet of Things: A Survey

Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014) · IEEE Communications Surveys & Tutorials

Context-Aware Activity Recognition SystemsIoT and Edge/Fog Computing

Cited by 2,861

Principles of early drug discovery

Hughes, J., Rees, S., Kalindjian, S., & Philpott, K. (2011) · British Journal of Pharmacology

Computational Drug Discovery MethodsAnimal testing and alternatives

Cited by 2,859

FitNets: Hints for Thin Deep Nets

Romero, A., Ballas, N., Kahou, S. E., Chassang, A., Gatta, C., & Bengio, Y. (2014) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 2,859

SimCSE: Simple Contrastive Learning of Sentence Embeddings

Gao, T., Yao, X., & Chen, D. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 2,851

Convolutional Sequence to Sequence Learning

Gehring, J., Auli, M., Grangier, D., Yarats, D., & Dauphin, Y. N. (2017) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 2,850

Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions

Zhao, G., & Pietikainen, M. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Image Retrieval and Classification TechniquesFace and Expression Recognition

Cited by 2,846

Structural Deep Network Embedding

Wang, D., Cui, P., & Zhu, W. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Advanced Graph Neural NetworksComplex Network Analysis Techniques

Cited by 2,845

A Survey on Evaluation of Large Language Models

Chang, Y., Wang, X., Wang, J., Wu, Y., Yang, L., Zhu, K., Chen, H., Yi, X., Wang, C., Wang, Y., et al. (2024) · ACM Transactions on Intelligent Systems and Technology

Topic ModelingNatural Language Processing Techniques

Cited by 2,842