Check computer science papers: citations, claims and retractions

Deformable Convolutional Networks

Dai, J., Qi, H., Xiong, Y., Li, Y., Zhang, G., Hu, H., & Wei, Y. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 7,513

Unified segmentation

Ashburner, J., & Friston, K. J. (2005) · NeuroImage

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 7,507

Extracting and composing robust features with denoising autoencoders

Vincent, P., Larochelle, H., Bengio, Y., & Manzagol, P.-A. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08

Neural Networks and ApplicationsFace and Expression Recognition

Cited by 7,436

Cascade R-CNN: Delving into High Quality Object Detection

Cai, Z., & Vasconcelos, N. (2017) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 7,408

Building a Large Annotated Corpus of English: The Penn Treebank

Marcus, M. (1993)

Natural Language Processing TechniquesSyntax, Semantics, Linguistic Variation

Cited by 7,405

Cascade R-CNN: Delving Into High Quality Object Detection

Cai, Z., & Vasconcelos, N. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 7,370

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

Ma, N., Zhang, X., Zheng, H.-T., & Sun, J. (2018) · Lecture notes in computer science

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 7,356

Dual Attention Network for Scene Segmentation

Fu, J., Liu, J., Tian, H., Li, Y., Bao, Y., Fang, Z., & Lu, H. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 7,351

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

Ma, N., Zhang, X., Zheng, H.-T., & Sun, J. (2018) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 7,344

ChatGPT for good? On opportunities and challenges of large language models for education

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences

Artificial Intelligence in EducationArtificial Intelligence in Healthcare and Education

Cited by 7,326

seaborn: statistical data visualization

Waskom, M. (2021) · Journal of Open Source Software

Computational Physics and Python ApplicationsData Visualization and Analytics

Cited by 7,310

Wide Residual Networks

Zagoruyko, S., & Komodakis, N. (2016) · Procedings of the British Machine Vision Conference 2016

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 7,244

Support vector machines

Hearst, M. A., Dumais, S. T., Osuna, E., Platt, J., & Scholkopf, B. (1998) · IEEE Intelligent Systems and their Applications

Machine Learning and AlgorithmsText and Document Classification Technologies

Cited by 7,243

Systematic review of research on artificial intelligence applications in higher education – where are the educators?

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education

Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

Cited by 7,242

The use of the area under the ROC curve in the evaluation of machine learning algorithms

Bradley, A. P. (1997) · Pattern Recognition

Imbalanced Data Classification TechniquesArtificial Intelligence in Healthcare

Cited by 7,217

An Algorithm for Vector Quantizer Design

Linde, Y., Buzo, A., & Gray, R. (1980) · IEEE Transactions on Communications

Advanced Data Compression TechniquesSpeech and Audio Processing

Cited by 7,201

Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors

Chou, T.-C., & Talalay, P. (1984) · Advances in Enzyme Regulation

Computational Drug Discovery Methodsthermodynamics and calorimetric analyses

Cited by 7,178

Asynchronous Methods for Deep Reinforcement Learning

Mnih, V., Badia, A. P., Mirza, M., Graves, A., Lillicrap, T. P., Harley, T., Silver, D., & Kavukcuoglu, K. (2016) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 7,132

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

McInnes, L., Healy, J., & Melville, J. (2018) · arXiv

Face and Expression RecognitionTopological and Geometric Data Analysis

Cited by 7,101

LSTM: A Search Space Odyssey

Greff, K., Srivastava, R. K., Koutník, J., Steunebrink, B. R., & Schmidhuber, J. (2015) · arXiv

Neural Networks and ApplicationsSpeech Recognition and Synthesis

Cited by 7,073

Thumbs up?: sentiment classification using machine learning techniques

Pang, B., Lee, L., & Vaithyanathan, S. (2002) · Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02

Sentiment Analysis and Opinion MiningText and Document Classification Technologies

Cited by 7,024

FCOS: Fully Convolutional One-Stage Object Detection

Tian, Z., Shen, C., Chen, H., & He, T. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 7,013

Fast approximate energy minimization via graph cuts

Boykov, Y., Veksler, O., & Zabih, R. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Medical Image Segmentation TechniquesAdvanced Vision and Imaging

Cited by 6,988

On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Topic ModelingEthics and Social Impacts of AI

Cited by 6,988