Search Results - multilayer convolutional sparse coding

An Improved Multilayer Convolutional Sparse Coding Model for Fault Feature Extraction of Rolling Element Bearings Under Varying Speed Conditions by Dong, Guangming

“… This article proposes an improved multilayer convolutional sparse coding (ML-CSC) model incorporating an overlap-crop (OC…”
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A convolutional neural network with sparse representation by Yang, Guoan, Yang, Junjie, Lu, Zhengzhi, Liu, Deyang

“…This paper proposes a sparse representation layer in the feature extraction stage of a convolutional neural network (CNN…”
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Towards understanding residual and dilated dense neural networks via convolutional sparse coding by Zhang, Zhiyang, Zhang, Shihua

“… However, a clear theoretical understanding of such networks is still lacking. Recently, a multilayer convolutional sparse coding (ML-CSC…”
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Multilayer Convolutional Sparse Modeling: Pursuit and Dictionary Learning by Sulam, Jeremias, Papyan, Vardan, Romano, Yaniv, Elad, Michael

“…The recently proposed multilayer convolutional sparse coding (ML-CSC) model, consisting of a cascade of convolutional sparse layers, provides a new interpretation of convolutional neural networks (CNNs…”
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Facial Expression Recognition based on Convolutional Neural Network with Sparse Representation by Liu, Xuan, Ma, Jiachen, Wang, Qiang

“… We use a sparse representation layer that is built by the Haar wavelet transform or shearlet transform prior to the convolutional layers of a standard CNN…”
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Multimodal Extension of the ML-CSC Framework for Medical Image Segmentation by Janssens, Jens, Lazendic, Srdan, Huang, Shaoguang, Pizurica, Aleksandra

“… Recently introduced Multilayer Convolutional Sparse Coding (ML-CSC) data model provides a model-based explanation of CNNs…”
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On Interpretability of CNNs for Multimodal Medical Image Segmentation by Lazendic, Srdan, Janssens, Jens, Huang, Shaoguang, Pizurica, Aleksandra

“… Multilayer Convolutional Sparse Coding (ML-CSC) data model, provides a model-based explanation of convolutional neural networks (CNNs…”
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SureUnet: sparse autorepresentation encoder U-Net for noise artifact suppression in low-dose CT by Liu, Jin, Zhang, Tingyu, Kang, Yanqin, Qiang, Jun, Hu, Dianlin, Zhang, Yikun

“…). First, inspired by multilayer convolutional sparse coding (CSC), we constructed a sparse autorepresentation encoder to sufficiently capture and represent hierarchical image features…”
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Multilayer Convolution Sparse Coding for Expression Recognition by Chen, Shuda, Wu, Yan

“… features and low recognition rates. Therefore, a new Multilayer Convolution Sparse Coding (MCSC…”
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Denoising Low-Dose CT Images Using a Multi-Layer Convolutional Analysis-Based Sparse Encoder Network by Kang, Yanqin, Liu, Jin, Liu, Tao, Qiang, Jun

“…). Inspired by convolutional sparse coding (CSC), we constructed a multilayer CASE to sufficiently capture and represent hierarchical image features and designed CASE-net to achieve improved LDCT noise artifact suppression…”
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Multi-layer Convolutional Sparse Coding Framework for Restoration of Under-sampled MR Images by Wahid, Abdul, Ullah, Abdul Wahab Usman, Kadir, Kushairy, Saadain, Syed

“…Magnetic Resonance Imaging (MRI) plays an important role in the diagnosis of different pathologies associated with human anatomy. The need to acquire images…”
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Convolutional Dictionary Learning in Hierarchical Networks by Zazo, Javier, Tolooshams, Bahareh, Ba, Demba, Paulson, Harvard John A.

“… This recursion describes a linear dynamic system that is a non-Gaussian Markov process across scales and is closely related to multilayer-convolutional sparse coding (ML-CSC…”
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Deep sparse representation driven network for compressive imaging by Shi, Baoshun, Li, Dan

“… Multilayer convolutional sparse coding (CSC), also known as deep sparse representation (deep SR), addresses this challenge by interpreting the forward process of DNNs…”
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Abnormal Traffic Detection System Based on Feature Fusion and Sparse Transformer by Zhao, Xinjian, Miao, Weiwei, Yuan, Guoquan, Jiang, Yu, Zhang, Song, Li, Qianmu

“…). FSTDS utilizes a feature fusion network to encode the traffic data sequences and extracting features, fusing them into coding vectors through shallow and deep convolutional networks, followed by deep…”
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CSC-Unet: A Novel Convolutional Sparse Coding Strategy Based Neural Network for Semantic Segmentation by Tang, Haitong, He, Shuang, Yang, Mengduo, Lu, Xia, Yu, Qin, Liu, Kaiyue, Yan, Hongjie, Wang, Nizhuan

“… for various application scenes. Thus, in this paper, we proposed a novel strategy that reformulated the popularly used convolution operation to multi-layer convolutional sparse coding block in semantic segmentation method to ease…”
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Deforestation rate estimation using crossbreed multilayer convolutional neural networks by Subhahan, D. Abdus, Kumar, C. N. S. Vinoth

“… Therefore, this study develops a cross-breed multilayer convolutional…”
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On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks by Sulam, Jeremias, Aberdam, Aviad, Beck, Amir, Elad, Michael

“… Motivated by the recent Multi-Layer Convolutional Sparse Coding (ML-CSC) model, we herein generalize the traditional Basis Pursuit problem to a multi-layer setting…”
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An Efficient Multilayer Spiking Convolutional Neural Network Processor for Object Recognition With Low Bitwidth and Channel-Level Parallelism by Feng, Lichen, Zhang, Yueqi, Zhu, Zhangming

“…Previous studies have shown that the event-driven multilayer spiking convolutional neural network (SCNN…”
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Multi Attention Convolutional Sparse Coding U-Net for Enhanced Land-Use and Land-Cover Segmentation Using Hyperspectral Images by Yele, Vijaykumar P., Badhe, Namdeo Baban, Alegavi, Sujata, Sedamkar, R. R.

“… with the architectural complexities hindering the performance across different datasets and tasks. In response to this, a Multi Attention Convolutional sparse coding U-network Feed-forward Network (MACUFN…”
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Convergence of Slice-Based Block Coordinate Descent Algorithm for Convolutional Sparse Coding by Wang, Jin-Jia, Wei, Xiao, Yu, Hui, Li, Jing

“…Convolutional sparse coding (CSC) models are becoming increasingly popular in the signal and image processing communities in recent years…”
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