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Top rated computer vision and pattern recognition
Here are some top-rated research papers and books on computer vision and pattern recognition:
Research Papers:
- "ImageNet Classification with Deep Convolutional Neural Networks" by Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton (2012) - This paper introduced the concept of deep neural networks for image classification and achieved state-of-the-art results on the ImageNet dataset.
- "Deep Residual Learning for Image Recognition" by Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun (2016) - This paper introduced the concept of residual learning and achieved state-of-the-art results on several image classification benchmarks.
- "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" by Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun (2015) - This paper introduced the Faster R-CNN object detection framework, which is widely used in computer vision applications.
- "U-Net: Convolutional Networks for Biomedical Image Segmentation" by Olaf Ronneberger, Philipp Fischer, and Thomas Brox (2015) - This paper introduced the U-Net architecture for image segmentation, which is widely used in medical image analysis.
- "Mask R-CNN" by Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick (2017) - This paper introduced the Mask R-CNN framework, which extends Faster R-CNN to include instance segmentation.
Books:
- "Computer Vision: Algorithms and Applications" by Richard Szeliski (2010) - This book provides a comprehensive overview of computer vision algorithms and applications.
- "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville (2016) - This book provides a detailed introduction to deep learning techniques, including those used in computer vision.
- "Pattern Recognition and Machine Learning" by Christopher M. Bishop (2006) - This book provides a comprehensive introduction to pattern recognition and machine learning techniques, including those used in computer vision.
- "Computer Vision: A Modern Approach" by David A. Forsyth and Jean Ponce (2011) - This book provides a comprehensive introduction to computer vision algorithms and applications.
- "Image Processing, Analysis, and Machine Vision" by Milan Sonka, Vaclav Hlavac, and Roger Boyle (2014) - This book provides a comprehensive introduction to image processing, analysis, and machine vision techniques.
Conferences:
- CVPR (Computer Vision and Pattern Recognition) - This is one of the top conferences in computer vision and pattern recognition, held annually by the IEEE.
- ICCV (International Conference on Computer Vision) - This is another top conference in computer vision, held bi-annually by the IEEE.
- NIPS (Conference on Neural Information Processing Systems) - This conference covers a wide range of topics in machine learning and deep learning, including computer vision.
- ECCV (European Conference on Computer Vision) - This is a bi-annual conference that covers a wide range of topics in computer vision.
- ICML (International Conference on Machine Learning) - This conference covers a wide range of topics in machine learning, including computer vision.
Journals:
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) - This is one of the top journals in computer vision and pattern recognition.
- International Journal of Computer Vision (IJCV) - This journal covers a wide range of topics in computer vision.
- IEEE Transactions on Image Processing (TIP) - This journal covers a wide range of topics in image processing and analysis.
- Computer Vision and Image Understanding (CVIU) - This journal covers a wide range of topics in computer vision and image understanding.
- Pattern Recognition (PR) - This journal covers a wide range of topics in pattern recognition and machine learning.
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