Results 41 to 50 of about 224,871 (275)
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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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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SpaRec: Sparse Systematic RLNC Recoding in Multi-Hop Networks
IEEE Access, 2021 Sparse Random Linear Network Coding (RLNC) reduces the computational complexity of the RLNC decoding through a low density of the non-zero coding coefficients, which can be achieved through sending uncoded (systematic) packets.
Elif Tasdemir +6 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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Fast Image Super-resolution with Sparse Coding
MATEC Web of Conferences, 2016 In this paper, we introduce a novel fast image reconstruction method for super-resolution (SR) base on sparse coding. This method combine online dictionary learning and a fast sparse coding way, both of which can improve the efficiency of the ...
Yuan Zhi-chao, Li Ben-tu
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Learning a Deep Representative Saliency Map With Sparse Tensors
IEEE Access, 2019 The past few years have witnessed the prosperity of establishing deep architectures for modeling complex structured data. In this paper, motivated by the hierarchical, multi-scale and sparse characteristics of Human Visual System (HVS), we advance a new ...
Shuyuan Yang, Quanwei Gao, Shigang Wang
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Kernel locality‐constrained sparse coding for head pose estimation
IET Computer Vision, 2016 In many situations, it would be practical for a computer system user interface to have a model of where a person is looking and what the user is paying attention to.
Hyunduk Kim +3 more
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Relating sparse and predictive coding to divisive normalization.
PLoS Computational BiologySparse coding, predictive coding and divisive normalization have each been found to be principles that underlie the function of neural circuits in many parts of the brain, supported by substantial experimental evidence.
Yanbo Lian, Anthony N Burkitt
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Convolutional sparse coding network for sparse seismic time-frequency representation
Artificial Intelligence in GeosciencesSeismic time-frequency (TF) transforms are essential tools in reservoir interpretation and signal processing, particularly for characterizing frequency variations in non-stationary seismic data.
Qiansheng Wei +5 more
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Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers
Molecular Oncology, EarlyView.This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel +6 more
wiley +1 more source