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Task-Driven Dictionary Learning [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience and signal processing. For signals such as natural images that admit such sparse representations, it is now well established that these models are well suited to restoration tasks.
Julien Mairal
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Some of the next articles are maybe not open access.
A novel dictionary learning named deep and shared dictionary learning for fault diagnosis
Mechanical Systems and Signal Processing, 2023Guangming Dong
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Multi-Modal Convolutional Dictionary Learning
IEEE Transactions on Image Processing, 2022Mai Xu, Fangyuan Gao, Xin Deng
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Joint patch clustering-based dictionary learning for multimodal image fusion
Information Fusion, 2016Hanseok Ko
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Label Consistent K-SVD: Learning a Discriminative Dictionary for Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013Zhuolin Jiang, Larry S Davis
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Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification
International Journal of Computer Vision, 2014Meng Yang, Xiangchu Feng
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Nonlinear dictionary learning with application to image classification
Pattern Recognition, 2018Junlin Hu, Yap-Peng Tan
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Fisher discrimination dictionary pair learning for image classification
Neurocomputing, 2017Weixin Luo, Meng Yang, Heyou Chang
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Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization
IEEE Transactions on Image Processing, 2014Ivor Wai-Hung Tsang, Shenghua Gao
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Discriminative analysis-synthesis dictionary learning for image classification
Neurocomputing, 2017Weixin Luo, Meng Yang, Heyou Chang
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