Results 31 to 40 of about 57,147 (259)
CoRR, 2012 We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic topic models, STC relaxes the normalization constraint of admixture proportions and the constraint of defining a normalized likelihood function.
Jun Zhu 0001, Eric P. Xing
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Sparse codes as Alpha Matte [PDF]
Proceedings of the British Machine Vision Conference 2014, 2014 In this paper, image matting is cast as a sparse coding problem wherein the sparse codes directly give the estimate of the alpha matte. Hence, there is no need to use the matting equation that restricts the estimate of alpha from a single pair of foreground (F) and background (B) samples.
Johnson, Jubin +2 more
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An Optimum Deraining Scheme using Sparse Coding
International Journal of Emerging Research in Engineering, Science, and Management, 2022 Rain streak removal is a challenging and interesting task of image processing where the rain streaks will be removed from an image with rain streaks. In the literature, a large number of proposals are made where rain streak removal is considered as image
A Hazarathaiah +4 more
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Transformational Sparse Coding
CoRR, 2017 A fundamental problem faced by object recognition systems is that objects and their features can appear in different locations, scales and orientations. Current deep learning methods attempt to achieve invariance to local translations via pooling, discarding the locations of features in the process.
Dimitrios C. Gklezakos, Rajesh P. N. Rao
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Sparse-Coding Variational Autoencoders [PDF]
Neural Computation, 2018 Abstract The sparse coding model posits that the visual system has evolved to efficiently code natural stimuli using a sparse set of features from an overcomplete dictionary. The original sparse coding model suffered from two key limitations; however: (1) computing the neural response to an image patch required minimizing a nonlinear ...
Victor Geadah +4 more
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Sparse representation of salient regions for no-reference image quality assessment
International Journal of Advanced Robotic Systems, 2016 This paper introduces an efficient feature learning framework via sparse coding for no-reference image quality assessment. The important part of the proposed framework is based on sparse feature extraction from a sparse representation matrix, which is ...
Tianpeng Feng +5 more
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Local structure preserving sparse coding for infrared target recognition. [PDF]
PLoS ONE, 2017 Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex.
Jing Han +3 more
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An Improved Robust Sparse Coding for Face Recognition with Disguise
International Journal of Advanced Robotic Systems, 2012 Robust vision-based face recognition is one of most challenging tasks for robots. Recently the sparse representation-based classification (SRC) has been proposed to solve the problem.
Dexing Zhong +3 more
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A Fast Sparse Coding Method for Image Classification
Applied Sciences, 2019 Image classification is an important problem in computer vision. The sparse coding spatial pyramid matching (ScSPM) framework is widely used in this field.
Mujun Zang +4 more
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Neural Sparse Topical Coding [PDF]
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018 Topic models with sparsity enhancement have been proven to be effective at learn- ing discriminative and coherent latent top- ics of short texts, which is critical to many scientific and engineering applica- tions. However, the extensions of these models require carefully tailored graphi- cal models and re-deduced inference al- gorithms, limiting their
Min Peng 0002 +6 more
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