Výsledky vyhledávání - "compression algorithms"

Lossy Compression: An Online Multi-Stage Technology for High-Fidelity Synchro- Waveform Measurements Autor Qiu, Wei, Yin, He, Wu, Yuru, Dong, Yuqing, Zheng, Yao, Yao, Wenxuan, Liu, Yilu

“…Effective real-time monitoring and analysis of distributed grids necessitate the use of synchro-waveform measurements, which capture almost all high-frequency…”
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An Evolving TinyML Compression Algorithm for IoT Environments Based on Data Eccentricity Autor Signoretti, Gabriel, Silva, Marianne, Andrade, Pedro, Silva, Ivanovitch, Sisinni, Emiliano, Ferrari, Paolo

“…Currently, the applications of the Internet of Things (IoT) generate a large amount of sensor data at a very high pace, making it a challenge to collect and…”
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TTHRESH: Tensor Compression for Multidimensional Visual Data Autor Ballester-Ripoll, Rafael, Lindstrom, Peter, Pajarola, Renato

“…Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they…”
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Fast Neural Representations for Direct Volume Rendering Autor Weiss, S., Hermüller, P., Westermann, R.

“…Despite the potential of neural scene representations to effectively compress 3D scalar fields at high reconstruction quality, the computational complexity of…”
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Visual Hull Series: A Coarse‐to‐Fine Low‐Poly Meshing Method for Urban Buildings Autor He, Haoran, Wang, Haiyan, Liu, Yanli, Xing, Guanyu, Zhang, Yanci

“…In recent years, multi‐view stereo (MVS) methods have been gaining increasing popularity in the 3D reconstruction of large‐scale urban scenes. However, due to…”
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DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks Autor Wiedemann, Simon, Kirchhoffer, Heiner, Matlage, Stefan, Haase, Paul, Marban, Arturo, Marinc, Talmaj, Neumann, David, Nguyen, Tung, Schwarz, Heiko, Wiegand, Thomas, Marpe, Detlev, Samek, Wojciech

“…In the past decade deep neural networks (DNNs) have shown state-of-the-art performance on a wide range of complex machine learning tasks. Many of these results…”
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End‐to‐End Compressed Meshlet Rendering Autor Mlakar, D., Steinberger, M., Schmalstieg, D.

“…In this paper, we study rendering of end‐to‐end compressed triangle meshes using modern GPU techniques, in particular, mesh shaders. Our approach allows us to…”
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Comments and Corrections Correction to "Data-Aware Adaptive Pruning Model Compression Algorithm Based on a Group Attention Mechanism and Reinforcement Learning" Autor Yang, Zhi, Zhai, Yuan, Xiang, Yi, Wu, Jianquan, Shi, Jinliang, Wu, Ying

“…In the above article <xref ref-type="bibr" rid="ref1">[1] , unfortunately, we had missed grant number CQYC20200309237 of the funding organization Chongqing…”
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Survey of Inter‐Prediction Methods for Time‐Varying Mesh Compression Autor Dvořák, Jan, Hácha, Filip, Arvanitis, Gerasimos, Podgorelec, David, Moustakas, Konstantinos, Váša, Libor

“…Time‐varying meshes (TVMs), that is mesh sequences with varying connectivity, are a greatly versatile representation of shapes evolving in time, as they allow…”
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Structured Compressed Sensing: From Theory to Applications Autor Duarte, M. F., Eldar, Y. C.

“…Compressed sensing (CS) is an emerging field that has attracted considerable research interest over the past few years. Previous review articles in CS limit…”
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Pebble-depth Autor Jordon, Liam, Maguire, Phil, Moser, Philippe

“…In this paper we introduce a new feasible notion of Bennett's logical depth based on pebble transducers. This notion is defined based on the difference between…”
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Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates Autor Cui, Laizhong, Su, Xiaoxin, Zhou, Yipeng, Pan, Yi

“…Federated Learning (FL) is an emerging decentralized learning framework through which multiple clients can collaboratively train a learning model. However, a…”
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Kronecker Compressive Sensing Autor Duarte, M. F., Baraniuk, R. G.

“…Compressive sensing (CS) is an emerging approach for the acquisition of signals having a sparse or compressible representation in some basis. While the CS…”
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Development of lossless compression algorithms for power system operational data Autor Sarkar, Subhra J, Kundu, Palash K, Sarkar, Gautam

“…Power system measurement is extremely crucial for the stable power system operation and results in the generation of bulk data. This enormous volume of data…”
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Image-Compression Techniques: Classical and “Region-of-Interest-Based” Approaches Presented in Recent Papers Autor Ungureanu, Vlad-Ilie, Negirla, Paul, Korodi, Adrian

“…Image compression is a vital component for domains in which the computational resources are usually scarce such as automotive or telemedicine fields. Also,…”
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A comprehensive evaluation of multiple video compression algorithms for preserving BVP signal quality Autor Zhou, Caiying, Ye, Xiaolang, Wei, Yuanwang, De Florio, Vincenzo, Sun, Hong, Zhan, Xinlong, Li, Yonggang, Wang, Chaochao, Zhang, Xianchao

“…Remote Photoplethysmography (rPPG) detects heartbeat-induced skin color changes via camera to extract the Blood Volume Pulse (BVP) signal, which helps measure…”
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A Fast Fractal Based Compression for MRI Images Autor Liu, Shuai, Bai, Weiling, Zeng, Nianyin, Wang, Shuihua

“…Magnetic resonance imaging (MRI), which assists doctors in determining clinical staging and expected surgical range, has high medical value. A large number of…”
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Data-Aware Adaptive Compression for Stream Processing Autor Zhang, Yu, Zhang, Feng, Li, Hourun, Zhang, Shuhao, Guo, Xiaoguang, Chen, Yuxing, Pan, Anqun, Du, Xiaoyong

“…Stream processing has been in widespread use, and one of the most common application scenarios is SQL query on streams. By 2021, the global deployment of IoT…”
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CStream: Parallel Data Stream Compression on Multicore Edge Devices Autor Zeng, Xianzhi, Zhang, Shuhao

“…In the burgeoning realm of Internet of Things (IoT) applications on edge devices, data stream compression has become increasingly pertinent. The integration of…”
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PAC: A monitoring framework for performance analysis of compression algorithms in Spark Autor Zhu, Changpeng, Han, Bo, Li, Gang

“…In Spark, a massive amount of immediate data inevitably leads to excessive I/O overhead. To mitigate this issue, Spark incorporates four compression algorithms…”
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