--- title: "Computer Vision and Pattern Recognition — papers" description: "Computer Vision and Pattern Recognition: 1,029 papers of the Elamur Research library · page 1 of 12 · 1–25, the most cited first — our summary of each…" canonical: "https://research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) / Computer Vision and Pattern Recognition # 👁️ Computer Vision and Pattern Recognition 1,029 papers · page 1 of 12 · 1–25 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Computer Vision and Pattern Recognition is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Multimodal Machine Learning Applications», «Advanced Neural Network Applications», «Handwritten Text Recognition Techniques». ## Papers **1** [2](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/2/) … [12](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/12/) [next →](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/2/) 1. [**Very Deep Convolutional Networks for Large-Scale Image Recognition**Karen Simonyan, Andrew Zisserman*2014 · 72,803 citations*](https://md.research.elamur.ai/free/en/papers/simonyan-2014-very-deep-convolutional-networks-large/) 2. [**Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks**Shaoqing Ren, Kaiming He, Ross Girshick, et al.*2015 · 64,743 citations*](https://md.research.elamur.ai/free/en/papers/ren-2015-faster-r-cnn-towards-real/) 3. [**Swin Transformer: Hierarchical Vision Transformer using Shifted Windows**Ze Liu, Yutong Lin, Yue Cao, et al.*2021 · 33,826 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-swin-transformer-hierarchical-vision-transformer/) 4. [**Rich feature hierarchies for accurate object detection and semantic segmentation**Ross Girshick, Jeff Donahue, Trevor Darrell, et al.*2013 · 31,715 citations*](https://md.research.elamur.ai/free/en/papers/girshick-2013-rich-feature-hierarchies-accurate-object/) 5. [**PyTorch: An Imperative Style, High-Performance Deep Learning Library**Adam Paszke, Sam Gross, Francisco Massa, et al.*2019 · 18,392 citations*](https://md.research.elamur.ai/free/en/papers/paszke-2019-pytorch-imperative-style-high-performance/) 6. [**End-to-End Object Detection with Transformers**Nicolas Carion, Francisco Massa, Gabriel Synnaeve, et al.*2020 · 16,761 citations*](https://md.research.elamur.ai/free/en/papers/carion-2020-end-end-object-detection-transformers/) 7. [**Convolutional Neural Networks for Sentence Classification**Yoon Kim*2014 · 16,218 citations*](https://md.research.elamur.ai/free/en/papers/kim-2014-convolutional-neural-networks-sentence-classification/) 8. [**Transformers: State-of-the-Art Natural Language Processing**Thomas Wolf, Lysandre Debut, Victor Sanh, et al.*2020 · 15,591 citations*](https://md.research.elamur.ai/free/en/papers/wolf-2020-transformers-state-art-natural-language/) 9. [**Distilling the Knowledge in a Neural Network**Geoffrey Hinton, Oriol Vinyals, Jeff Dean*2015 · 15,026 citations*](https://md.research.elamur.ai/free/en/papers/hinton-2015-distilling-knowledge-neural-network/) 10. [**Momentum Contrast for Unsupervised Visual Representation Learning**Kaiming He, Haoqi Fan, Yuxin Wu, et al.*2019 · 13,143 citations*](https://md.research.elamur.ai/free/en/papers/he-2019-momentum-contrast-unsupervised-visual-representation/) 11. [**FaceNet: A Unified Embedding for Face Recognition and Clustering**Florian Schroff, Dmitry Kalenichenko, James Philbin*2015 · 11,939 citations*](https://md.research.elamur.ai/free/en/papers/schroff-2015-facenet-unified-embedding-face-recognition/) 12. [**A Comprehensive Survey on Graph Neural Networks**Zonghan Wu, Shirui Pan, Fengwen Chen, et al.*2019 · 10,295 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/) 13. [**MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications**Andrew G. Howard, Menglong Zhu, Bo Chen, et al.*2017 · 9,633 citations*](https://md.research.elamur.ai/free/en/papers/howard-2017-mobilenets-efficient-convolutional-neural-networks/) 14. [**TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems**Martín Abadi, Ashish Agarwal, Paul Barham, et al.*2016 · 9,453 citations*](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/) 15. [**Graph Attention Networks**Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al.*2017 · 8,996 citations*](https://md.research.elamur.ai/free/en/papers/veli-vckovic-2017-graph-attention-networks/) 16. [**Semi-Supervised Classification with Graph Convolutional Networks**Thomas N. Kipf, Max Welling*2016 · 8,809 citations*](https://md.research.elamur.ai/free/en/papers/kipf-2016-semi-supervised-classification-graph-convolutional/) 17. [**Learning Transferable Visual Models From Natural Language Supervision**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,295 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/) 18. [**A Simple Framework for Contrastive Learning of Visual Representations**Ting Chen, Simon Kornblith, Mohammad Norouzi, et al.*2020 · 7,774 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-simple-framework-contrastive-learning-visual/) 19. [**Show, Attend and Tell: Neural Image Caption Generation with Visual Attention**Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.*2015 · 7,483 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/) 20. [**UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction**Leland McInnes, John Healy, James Melville*2018 · 7,136 citations*](https://md.research.elamur.ai/free/en/papers/mcinnes-2018-umap-uniform-manifold-approximation-projection/) 21. [**Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks**Alec Radford, Luke Metz, Soumith Chintala*2015 · 6,519 citations*](https://md.research.elamur.ai/free/en/papers/radford-2015-unsupervised-representation-learning-deep-convolutional/) 22. [**Learning Transferable Architectures for Scalable Image Recognition**Barret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.*2017 · 6,518 citations*](https://md.research.elamur.ai/free/en/papers/zoph-2017-learning-transferable-architectures-scalable-image/) 23. [**Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization**Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, et al.*2016 · 6,327 citations*](https://md.research.elamur.ai/free/en/papers/selvaraju-2016-grad-cam-visual-explanations-deep/) 24. [**Emerging Properties in Self-Supervised Vision Transformers**Mathilde Caron, Hugo Touvron, Ishan Misra, et al.*2021 · 5,910 citations*](https://md.research.elamur.ai/free/en/papers/caron-2021-emerging-properties-self-supervised-vision/) 25. [**Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations**Ranjay Krishna, Yuke Zhu, Oliver Groth, et al.*2016 · 5,747 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2016-visual-genome-connecting-language-vision/) **1** [2](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/2/) … [12](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/12/) [next →](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/2/) Updated 23 October 2026 - [← previous subfield Computer Science Applications](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-science-applications/) - [next subfield → Hardware and Architecture](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) - [↑ back to Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/)