Search Results - "convolutional sparse coding"

Deep Convolutional Neural Network for Multi-Modal Image Restoration and Fusion by Deng, Xin, Dragotti, Pier Luigi

“…In this paper, we propose a novel deep convolutional neural network to solve the general multi-modal image restoration (MIR) and multi-modal image fusion (MIF)…”
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Multistate fault diagnosis strategy for bearings based on an improved convolutional sparse coding with priori periodic filter group by Han, Changkun, Lu, Wei, Wang, Huaqing, Song, Liuyang, Cui, Lingli

“…[Display omitted] •A multistate fault diagnosis model for bearings based on PPFG/ICSC is proposed.•The construction and parameter selection method of PPFG is…”
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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…”
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Interpretable Multi-modal Image Registration Network Based on Disentangled Convolutional Sparse Coding by Deng, Xin, Liu, Enpeng, Li, Shengxi, Duan, Yiping, Xu, Mai

“…Multi-modal image registration aims to spatially align two images from different modalities to make their feature points match with each other. Captured by…”
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Convolutional Sparse Coding for Compressed Sensing CT Reconstruction by Bao, Peng, Sun, Huaiqiang, Wang, Zhangyang, Zhang, Yi, Xia, Wenjun, Yang, Kang, Chen, Weiyan, Chen, Mianyi, Xi, Yan, Niu, Shanzhou, Zhou, Jiliu, Zhang, He

“…Over the past few years, dictionary learning (DL)-based methods have been successfully used in various image reconstruction problems. However, the traditional…”
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Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding by Papyan, Vardan, Sulam, Jeremias, Elad, Michael

“…The celebrated sparse representation model has led to remarkable results in various signal processing tasks in the last decade. However, despite its initial…”
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Convolutional Dictionary Learning: Acceleration and Convergence by Chun, Il Yong, Fessler, Jeffrey A.

“…Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in…”
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A method of reconstructing compressive spectral imaging with a complementary prior constraint by Wang, Pan, Li, Jie, Qi, Chun, Wang, Lin, Wang, Feng ping

“…Compressed spectral imaging (CSI) is a technique for acquiring a cube of spectral image data in a single snapshot. In this paper, we propose a reconstruction…”
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An Improved Multilayer Convolutional Sparse Coding Model for Fault Feature Extraction of Rolling Element Bearings Under Varying Speed Conditions by Dong, Guangming

“…Rolling element bearings are critical components in rotating machinery, and their faults often lead to machinery failure. Accurate fault diagnosis under…”
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Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications by Chang, Hang, Han, Ju, Zhong, Cheng, Snijders, Antoine M., Mao, Jian-Hua

“…The capabilities of (I) learning transferable knowledge across domains; and (II) fine-tuning the pre-learned base knowledge towards tasks with considerably…”
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Poisson2Poisson-Sparse: Unsupervised Poisson noise image denoising based on sparse modeling by Xiao, Lingzhi, Wang, Shengbiao, Zhang, Jun, Wei, Jiuzhe, Yang, Shihua

“…In fields such as low-light photography, astronomical imaging, and low-dose computed tomography scanning, Poisson noise severely degrades image quality due to…”
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An improved theoretical analysis of convolutional sparse coding using stripe coherence by Li, Haifeng, Chen, Wengu

“…Convolutional sparse coding has proven to be very effective in a wide range of applications. Recent work addressed the theoretical performance of global…”
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WARP-LCA: Efficient convolutional sparse coding with Locally Competitive Algorithm by Kasenbacher, Geoffrey, Ehret, Felix, Ecke, Gerrit, Otte, Sebastian

“…The locally competitive algorithm (LCA) can solve sparse coding problems across a wide range of use cases. Recently, convolution-based LCA approaches have been…”
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Convolutional Sparse Coding Based Channel Estimation for OTFS-SCMA in Uplink by Thomas, Anna, Deka, Kuntal, Raviteja, Patchava, Sharma, Sanjeev

“…Orthogonal time frequency space (OTFS) has emerged as the most sought-after modulation technique in a high mobility scenario. Sparse code multiple access…”
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Convolutional Sparse Coding for RGB+NIR Imaging by Xuemei Hu, Heide, Felix, Qionghai Dai, Wetzstein, Gordon

“…Emerging sensor designs increasingly rely on novel color filter arrays (CFAs) to sample the incident spectrum in unconventional ways. In particular, capturing…”
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Sparsity-Enhanced Convolutional Decomposition: A Novel Tensor-Based Paradigm for Blind Hyperspectral Unmixing by Yao, Jing, Hong, Danfeng, Xu, Lin, Meng, Deyu, Chanussot, Jocelyn, Xu, Zongben

“…Blind hyperspectral unmixing (HU) has long been recognized as a crucial component in analyzing the hyperspectral imagery (HSI) collected by airborne and…”
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On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks by Sulam, Jeremias, Aberdam, Aviad, Beck, Amir, Elad, Michael

“…Parsimonious representations are ubiquitous in modeling and processing information. Motivated by the recent Multi-Layer Convolutional Sparse Coding (ML-CSC)…”
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Tensor completion via convolutional sparse coding with small samples-based training by Liao, Tianchi, Wu, Zhebin, Chen, Chuan, Zheng, Zibin, Zhang, Xiongjun

“…•To tackle the missing value problem, we proposed two CSC regularized LRTC models, SNN-based and TNN-based, respectively.•In both models, an overcomplete…”
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Online Rain/Snow Removal from Surveillance Videos by Li, Minghan, Cao, Xiangyong, Zhao, Qian, Zhang, Lei, Meng, Deyu

“…Video rain/snow removal from surveillance videos is an important task in the computer vision community since rain/snow existed in videos can severely…”
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Motion deblurring via multiscale residual convolutional dictionary learning by Zhang, Yi, Chandler, Damon M., Farias, Mylène C.Q.

“…Sparsity-based methods have been extensively used for restoration of blurry images. To overcome the limitation found in patch-based sparse representation…”
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