Výsledky vyhľadávania - "Reconstruction algorithms"

A Systematic Review of Compressive Sensing: Concepts, Implementations and Applications Autor Rani, Meenu, Dhok, S. B., Deshmukh, R. B.

“…Compressive Sensing (CS) is a new sensing modality, which compresses the signal being acquired at the time of sensing. Signals can have sparse or compressible…”
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Deep Convolutional Neural Network for Inverse Problems in Imaging Autor Jin, Kyong Hwan, McCann, Michael T., Froustey, Emmanuel, Unser, Michael

“…In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative…”
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Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture Autor Assran, Mahmoud, Duval, Quentin, Misra, Ishan, Bojanowski, Piotr, Vincent, Pascal, Rabbat, Michael, LeCun, Yann, Ballas, Nicolas

“…This paper demonstrates an approach for learning highly semantic image representations without relying on hand-crafted data-augmentations. We introduce the…”
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Image Compressed Sensing Using Convolutional Neural Network Autor Shi, Wuzhen, Jiang, Feng, Liu, Shaohui, Zhao, Debin

“…In the study of compressed sensing (CS), the two main challenges are the design of sampling matrix and the development of reconstruction method. On the one…”
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Likelihood-Scheduled Score-Based Generative Modeling for Fully 3D PET Image Reconstruction Autor Webber, George, Mizuno, Yuya, Howes, Oliver D., Hammers, Alexander, King, Andrew P., Reader, Andrew J.

“…Medical image reconstruction with pre-trained score-based generative models (SGMs) has advantages over other existing state-of-the-art deep-learned…”
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Vector Bending Sensor Based on Low-Cost Single-Channel Measurement and Highly Reliable Three-Peak Reconstruction Algorithm Autor Li, Xiyu, Liu, Yi, Li, Yan, Qu, Shiliang

“…A vector bending sensor based on low-cost single-channel measurement and a highly reliable three-peak reconstruction algorithm is proposed. The sensor consists…”
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Model Stealing Attacks Against Inductive Graph Neural Networks Autor Shen, Yun, He, Xinlei, Han, Yufei, Zhang, Yang

“…Many real-world data come in the form of graphs. Graph neural networks (GNNs), a new family of machine learning (ML) models, have been proposed to fully…”
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From Denoising to Compressed Sensing Autor Metzler, Christopher A., Maleki, Arian, Baraniuk, Richard G.

“…A denoising algorithm seeks to remove noise, errors, or perturbations from a signal. Extensive research has been devoted to this arena over the last several…”
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SnS₂/WSe₂ van der Waals Single-Detector Spectrometer With a Dynamically Selecting Spectral Reconstruction Strategy Autor Zhou, Yang, Mu, Haoran, Zhang, Congwen, Xu, Renjing, Zhang, Guangyu, Lin, Shenghuang

“…The single-detector spectrometers based on 2D layer van der Waals (vdW) heterojunctions offer advantages in spectral reconstruction due to their high…”
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Coded Trace Reconstruction Autor Cheraghchi, Mahdi, Gabrys, Ryan, Milenkovic, Olgica, Ribeiro, Joao

“…Motivated by average-case trace reconstruction and coding for portable DNA-based storage systems, we initiate the study of coded trace reconstruction , the…”
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Neural 3D Scene Reconstruction with the Manhattan-world Assumption Autor Guo, Haoyu, Peng, Sida, Lin, Haotong, Wang, Qianqian, Zhang, Guofeng, Bao, Hujun, Zhou, Xiaowei

“…This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view images. Many previous works have shown impressive reconstruction results…”
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RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection Autor Zhang, Ximiao, Xu, Min, Zhou, Xiuzhuang

“…Self-supervised feature reconstruction methods have shown promising advances in industrial image anomaly de-tection and localization. Despite this progress,…”
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Learning to Recover 3D Scene Shape from a Single Image Autor Yin, Wei, Zhang, Jianming, Wang, Oliver, Niklaus, Simon, Mai, Long, Chen, Simon, Shen, Chunhua

“…Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art methods cannot be used to recover accurate 3D scene shape due…”
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Deep Learning Computed Tomography: Learning Projection-Domain Weights From Image Domain in Limited Angle Problems Autor Wurfl, Tobias, Hoffmann, Mathis, Christlein, Vincent, Breininger, Katharina, Huang, Yixin, Unberath, Mathias, Maier, Andreas K.

“…In this paper, we present a new deep learning framework for 3-D tomographic reconstruction. To this end, we map filtered back-projection-type algorithms to…”
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Robust Dynamic Radiance Fields Autor Liu, Yu-Lun, Gao, Chen, Meuleman, Andreas, Tseng, Hung-Yu, Saraf, Ayush, Kim, Changil, Chuang, Yung-Yu, Kopf, Johannes, Huang, Jia-Bin

“…Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene. Existing methods, however, assume that…”
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Compressive Sensing Based Image Codec With Partial Pre-Calculation Autor Xu, Jiayao, Yang, Jian, Kimishima, Fuma, Taniguchi, Ittetsu, Zhou, Jinjia

“…Compressive Sensing (CS) surpasses the limitations of the sampling theorem by reducing signal dimensions during sampling. Recent works integrate measurement…”
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Blind Recognition of 5G LDPC Codes Over a Candidate Set Autor Wang, Yuan, Che, Shuling

“…Blind recognition of channel codes is an important technology in Adaptive Modulation and Coding (AMC) systems. Shortening and puncturing have been adopted to…”
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A Sparse-View CT Reconstruction Method Based on Combination of DenseNet and Deconvolution Autor Zhang, Zhicheng, Liang, Xiaokun, Dong, Xu, Xie, Yaoqin, Cao, Guohua

“…Sparse-view computed tomography (CT) holds great promise for speeding up data acquisition and reducing radiation dose in CT scans. Recent advances in…”
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Simultaneous Coordinate Maximization Algorithm for Maximum A Posteriori Compton Camera Imaging With Markov Random Field Prior Autor Le, Nhan, Snoussi, Hichem, Iltis, Alain

“…It is widely acknowledged that maximum a posteriori (MAP) estimation, when combined with a Markov random field (MRF) prior, is an effective tool for Compton…”
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DRONE: Dual-Domain Residual-based Optimization NEtwork for Sparse-View CT Reconstruction Autor Wu, Weiwen, Hu, Dianlin, Niu, Chuang, Yu, Hengyong, Vardhanabhuti, Varut, Wang, Ge

“…Deep learning has attracted rapidly increasing attention in the field of tomographic image reconstruction, especially for CT, MRI, PET/SPECT, ultrasound and…”
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