Beyond ℓ1 sparse coding in V1. [PDF]
PLoS Computational Biology, 2023 Growing evidence indicates that only a sparse subset from a pool of sensory neurons is active for the encoding of visual stimuli at any instant in time.
Ilias Rentzeperis +3 more
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Semi-Supervised Sparse Coding [PDF]
2014 International Joint Conference on Neural Networks (IJCNN), 2015 Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised ...
Gao, Xin, Wang, Jim Jing-Yan
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Sparse coding models can exhibit decreasing sparseness while learning sparse codes for natural images. [PDF]
PLoS Computational Biology, 2013 The sparse coding hypothesis has enjoyed much success in predicting response properties of simple cells in primary visual cortex (V1) based solely on the statistics of natural scenes. In typical sparse coding models, model neuron activities and receptive
Joel Zylberberg, Michael Robert DeWeese
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Fast Approximation for Sparse Coding with Applications to Object Recognition [PDF]
Sensors, 2021 Sparse Coding (SC) has been widely studied and shown its superiority in the fields of signal processing, statistics, and machine learning. However, due to the high computational cost of the optimization algorithms required to compute the sparse feature ...
Zhenzhen Sun, Yuanlong Yu
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Structural Smoothing Low-Rank Matrix Restoration Based on Sparse Coding and Dual-Weighted Model [PDF]
Entropy, 2022 Group sparse coding (GSC) uses the non-local similarity of images as constraints, which can fully exploit the structure and group sparse features of images.
Jiawei Wu, Hengyou Wang
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Flash-Based Computing-in-Memory Architecture to Implement High-Precision Sparse Coding [PDF]
Micromachines, 2023 To address the concerns with power consumption and processing efficiency in big-size data processing, sparse coding in computing-in-memory (CIM) architectures is gaining much more attention.
Yueran Qi +9 more
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Simultaneous Patch-Group Sparse Coding with Dual-Weighted ℓp Minimization for Image Restoration [PDF]
Micromachines, 2021 Sparse coding (SC) models have been proven as powerful tools applied in image restoration tasks, such as patch sparse coding (PSC) and group sparse coding (GSC). However, these two kinds of SC models have their respective drawbacks. PSC tends to generate
Jiachao Zhang, Ying Tong, Liangbao Jiao
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Sparse Spectrotemporal Coding of Sounds [PDF]
EURASIP Journal on Advances in Signal Processing, 2003 Recent studies of biological auditory processing have revealed that sophisticated spectrotemporal analyses are performed by central auditory systems of various animals.
Körding Konrad P +2 more
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Hierarchical Sparse Coding of Objects in Deep Convolutional Neural Networks [PDF]
Frontiers in Computational Neuroscience, 2020 Recently, deep convolutional neural networks (DCNNs) have attained human-level performances on challenging object recognition tasks owing to their complex internal representation.
Xingyu Liu, Zonglei Zhen, Jia Liu
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Neural correlates of sparse coding and dimensionality reduction. [PDF]
PLoS Computational Biology, 2019 Supported by recent computational studies, there is increasing evidence that a wide range of neuronal responses can be understood as an emergent property of nonnegative sparse coding (NSC), an efficient population coding scheme based on dimensionality ...
Michael Beyeler +4 more
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