Learned distributed image compression with decoder side information by Yankai Yin, Zhe Sun, Peiying Ruan, Ruidong Li, Feng Duan

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Analysis of video image compression methods with partial information loss for medical information and measurement systems by Yu.O. Podchashynskyi, A.G. Stupak, L.O. Chepiuk

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Information Bottleneck Driven Deep Video Compression—IBOpenDVCW by Timor Leiderman, Yosef Ben Ezra

Subjects: “…deep video compression…”
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Quantum secure communication algorithm based on cyclic code and information compression by Hongyang MA, Xin ZHANG, Peng’ao XU, Fen LIU, Xingkui FAN

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Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
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Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
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A metric of knowledge as information compression reflects reproducibility predictions for biomedical experiments by Daniele Fanelli, Pedro Batista Tan, Olavo B. Amaral, Kleber Neves

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Adaptive information-constrained mapping for feature compression in edge AI and federated systems by Viacheslav Kovtun

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Application of wavelet transform for image compression in information-measuring systems for medical use by A.G. Stupak, Yu.O. Podchashynskyi, L.O. Chepiuk, O.A. Levkivskyi

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Efficient distributed storage strategy based on compressed sensing for space information network by Bo Kong, Gengxin Zhang, Wei Zhang, Dongming Bian, Zhidong Xie

“…This article investigates the distributed data storage problem with compressed sensing in the space information network. …”
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Research and application of flight trajectory data compression algorithm by YANG Yao, XIAO Yajuan

Subjects: “…flight trajectory|data compression|entropy of information|clustering…”
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Block-Based Adaptive Compressed Sensing by Using Edge Information for Real-Time Reconstruction by V. Pavitra, V. B. S. Srilatha Indira Dutt

“…Taking number of measurements adaptively based on information contained in each block of the image, results in better quality of recovered image, and is paving ways for general purpose use of compressed sensing in various applications. …”
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The Research on Image Adaptive Block Compressive Sensing Method Based on Underwater Depth Information by Shoubo Zhao, Jing Wang, Cheng Qian, Yue Yin

“…To address this issue, this paper innovatively proposes a compound depth-based adaptive block compressed sensing method (CD-ABCS). The compound depth matrix that is correlated with underwater depth information, image saliency and image variance is used to set sampling rate of the image block. …”
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A Novel Compressive Optical Encryption via Single-Pixel Imaging by Chenggong Zhang, Bennian Han, Wenqi He, Xiang Peng, Chen Xu

Subjects: “…Information security…”
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Compression rates of microbial genomes are associated with genome size and base composition by Jon Bohlin, John H.-O. Pettersson

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Algorithmic Support of Adaptive Automatic Control Systems with Data Compression by V. V. Alekseev, E. M. Antonyuk, I. E. Varshavskiy

Subjects: “…information and measuring system…”
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Discrete Cosine Transform-Based Joint Spectral–Spatial Information Compression and Band-Correlation Calculation for Hyperspectral Feature Extraction by Ziqi Zhao, Changbao Yang, Zhongjun Qiu, Qiong Wu

“…In SSBC features, joint spectral–spatial feature extraction is considered a discrete cosine transform-based information compression, where a flattening operation is used to avoid the high computational cost induced by the requirement of distillation from 3D images for joint spectral–spatial information. …”
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Robust Steganographic Method with Code-Controlled Information Embedding by Kobozeva A.A., Sokolov A.V

“…In view of the fact that most images are compressed when transmitted through telecommunica-tion systems and telecommunication systems in the energetics, from the point of view of the practical use of steganographic algorithms in real information security systems, such as their property, the ability to effectively resist a compression attack, is of great interest. …”
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Mixed precision quantization based on information entropy by Ting Qin, Zhao Li, Jiaqi Zhao, Yuting Yan, Yafei Du

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Spatial Compression in Memory: How Repeated Walks on Familiar Routes Shorten Perceived Distance by Kyung Wook Seo, Hyung-Sook Lee, Joo Young Kim

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