Results 251 to 260 of about 3,038,089 (290)
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Sparse Coding Guided Spatiotemporal Feature Learning for Abnormal Event Detection in Large Videos
IEEE transactions on multimedia, 2019Abnormal event detection in large videos is an important task in research and industrial applications, which has attracted considerable attention in recent years.
Wenqing Chu +3 more
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Supervised Deep Sparse Coding Networks for Image Classification
IEEE Transactions on Image Processing, 2020In this paper, we propose a novel deep sparse coding network (SCN) capable of efficiently adapting its own regularization parameters for a given application.
Xiaoxia Sun, N. Nasrabadi, T. Tran
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Order Preserving Sparse Coding
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015In this paper, we investigate order-preserving sparse coding for classifying structured data whose atomic features possess ordering relationships. Examples include time sequences where individual frame-wise features are temporally ordered, as well as still images (landscape, street view, etc.) where different regions of the image are spatially ordered.
Bingbing, Ni +2 more
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A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising
European Conference on Computer Vision, 2018Most of existing image denoising methods assume the corrupted noise to be additive white Gaussian noise (AWGN). However, the realistic noise in real-world noisy images is much more complex than AWGN, and is hard to be modeled by simple analytical ...
Jun Xu, Lei Zhang, D. Zhang
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Video Rain Streak Removal by Multiscale Convolutional Sparse Coding
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018Videos captured by outdoor surveillance equipments sometimes contain unexpected rain streaks, which brings difficulty in subsequent video processing tasks. Rain streak removal from a video is thus an important topic in recent computer vision research. In
Minghan Li +6 more
semanticscholar +1 more source
Neurocomputing, 2014
Sparse coding has received an increasing amount of interest in recent years. It finds a basis set that captures high-level semantics in the data and learns sparse coordinates in terms of the basis set. However, most of the existing approaches fail to consider the geometrical structure of the data space.
Miao Zheng, Jiajun Bu, Chun Chen
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Sparse coding has received an increasing amount of interest in recent years. It finds a basis set that captures high-level semantics in the data and learns sparse coordinates in terms of the basis set. However, most of the existing approaches fail to consider the geometrical structure of the data space.
Miao Zheng, Jiajun Bu, Chun Chen
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Convolution Structure Sparse Coding for Fusion of Panchromatic and Multispectral Images
IEEE Transactions on Geoscience and Remote Sensing, 2019Recently, sparse coding-based image fusion methods have been developed extensively. Although most of them can produce competitive fusion results, three issues need to be addressed: 1) these methods divide the image into overlapped patches and process ...
Kai Zhang +3 more
semanticscholar +1 more source
Proceedings of the 27th ACM SIGPLAN-SIGACT symposium on Principles of programming languages, 2000
In this article, we add a third dimension to partial redundancy elimination by considering code size as a further optimization goal in addition to the more classical consideration of computation costs and register pressure. This results in a family of sparse code motion algorithms coming as modular extensions of the algorithms for busy and lazy code ...
Oliver Rüthing +2 more
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In this article, we add a third dimension to partial redundancy elimination by considering code size as a further optimization goal in addition to the more classical consideration of computation costs and register pressure. This results in a family of sparse code motion algorithms coming as modular extensions of the algorithms for busy and lazy code ...
Oliver Rüthing +2 more
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2011
1.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1 The stabilized auditory image . . . . . . . . . . . . . .
Steven Ness +2 more
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1.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1 The stabilized auditory image . . . . . . . . . . . . . .
Steven Ness +2 more
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Sparse Autoencoder for Sparse Code Multiple Access
2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 2021In the forthcoming 5G technology, Sparse Code Multiple Access (SCMA) is the most promising scheme that aims at improving spectral efficiency further and providing massive connectivity. The challenge behind implementing SCMA scheme is: constructing optimized codebooks in order to obtain minimum BER while keeping the receiver complexity minimum.
Medini Singh, Deepak Mishra, M. Vanidevi
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