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检索条件"主题词=compression algorithms"

共 2082 条记录，以下是261-270 订阅

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Storage of key Features of Images of Sulfur Imprints in the Mathematical Structure Form

Storage of key Features of Images of Sulfur Imprints in the ...

引用

International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： I.I. Bagaev O.S. Logunova Institute of Energy and Automated Systems Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (数字)9781728169514

ISBN: (纸本)9781728169521

The aim of the study is to develop a method for storing images of sulfur imprints. In the framework of the study, a more effective method of representing images of sulfur imprints by using knowledge of the specificity of these images was developed compared to universal methods. In particular, a method for storing images of sulfur imprints has been developed, which stores information about objects that are significant for technological analysis in the image. The developed method was tested for images of sulfur imprints of continuously cast billets for the conditions of a large metallurgical enterprise in Russia. To conduct a computational experiment, a software product was designed and developed that allows you to convert the image of a sulfur imprint into a mathematical representation, as well as the process of restoring the main image. Using the array of retrospective information of 2011-2018 and the developed software product, the calculation of the effectiveness of the presentation of graphic information in the form of a structural unit of information without directly saving the image was performed. The average share of stored information from the original volume is 0.53 percent.

关键词： Image coding Graphics Sulfur Software Transform coding compression algorithms Brightness

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Bandwidth Efficient Near-Storage Accelerator for High-Dimensional Similarity Search

Bandwidth Efficient Near-Storage Accelerator for High-Dimens...

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IEEE International Conference on Field-Programmable Technology (FPT)

作者： Gongjin Sun Sang-Woo Jun University of California Irvine

ISBN: (纸本)9781665423021;9781665446228

Performance of high-dimensional similarity search systems is often determined by the rate of distance calculation between a query and candidate neighbors. This is because as the dimensionality of data becomes higher, it suffers the so-called “curse of dimensionality”, which makes conventional indexing methods inefficient. Since the sheer size of datasets of interest often mandate storing them in secondary storage, this means the performance of a similarity search may be primarily limited by the storage device bandwidth, especially if the distance calculation can be offloaded to a high-performance accelerator built with GPUs or FPGAs. In this paper, we present ZipNN, which moves the bottleneck away from the storage performance in order to make more effective use of available computation resources. We achieve this via two approaches: First, ZipNN is a near-storage accelerator which takes advantage of the high internal bandwidth of storage. Second, it implements multiple pipelines of an application-optimized, wire-speed compression algorithm which can handle full storage bandwidth. We evaluate ZipNN using real-world datasets and an FPGA-based implementation. Compared to a comparable FPGA accelerator deployed in a standalone device, it demonstrates over 6× performance improvements. It also delivers an order of magnitude improvement compared to a purely software implementation.

关键词： Performance evaluation Pipelines Bandwidth Software Field programmable gate arrays compression algorithms Indexing

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Fully Convolutional Network for Removing DCT Artefacts From Images

Fully Convolutional Network for Removing DCT Artefacts From ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Patryk Najgebauer Rafał Scherer Leszek Rutkowski Częstochowa University of Technology Częstochowa Poland Information Technology Institute University of Social Sciences Lodz Poland

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Image compression is one of the essential methods of image processing. Its most prominent advantage is the significant reduction of image size allowing for more efficient storage and transfer. However, lossy compression is associated with the loss of some image details in favor of reducing its size. In compressed images, the deficiencies are manifested by noticeable defects in the form of artifacts; the most common are block artifacts, ringing effect, or blur. In this article, we propose three models of fully convolutional networks with different configurations and examine their abilities in reducing compression artifacts. In the experiments, we research the extent to which the results are improved for models that will process the image in a similar way to the compression algorithm, and whether the initialization with predefined filters would allow for better image reconstruction than developed solely during learning.

关键词： Image coding Discrete cosine transforms Transform coding compression algorithms Neural networks Noise measurement Kernel

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Intermittent Inference with Nonuniformly Compressed Multi-Exit Neural Network for Energy Harvesting Powered Devices

Intermittent Inference with Nonuniformly Compressed Multi-Ex...

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Design Automation Conference

作者： Yawen Wu Zhepeng Wang Zhenge Jia Yiyu Shi Jingtong Hu Department of Electrical and Computer Engineering University of Pittsburgh USA Department of Computer Science and Engineering University of Notre Dame USA

ISBN: (数字)9781728110851

ISBN: (纸本)9781728158020

This work aims to enable persistent, event-driven sensing and decision capabilities for energy-harvesting (EH)-powered devices by deploying lightweight DNNs onto EH-powered devices. However, harvested energy is usually weak and unpredictable and even lightweight DNNs take multiple power cycles to finish one inference. To eliminate the indefinite long wait to accumulate energy for one inference and to optimize the accuracy, we developed a power trace-aware and exit-guided network compression algorithm to compress and deploy multi-exit neural networks to EH-powered microcontrollers (MCUs) and select exits during execution according to available energy. The experimental results show superior accuracy and latency compared with state-of-the-art techniques.

关键词： Sensors Runtime Quantization (signal) Neural networks compression algorithms Energy harvesting Microcontrollers

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Motion compensation method for video encoding

Motion compensation method for video encoding

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Moscow Workshop on Electronic and Networking Technologies (MWENT)

作者： E. V. Medvedeva A. P. Metelev E. C. Kryshkina Department of Radio Electronics Vyatka State University VyatSU Kirov Russia

ISBN: (数字)9781728125725

ISBN: (纸本)9781728125732

A motion compensation method for video coding is proposed. The method is based at the estimation of motion vectors along the bit sheets of the most informative high order bits and the adaptive technology for selecting block sizes for motion compensation. Evaluation of motion vectors along the bit sheets of the higher bits will significantly reduce the computational complexity and enumeration of possible blocks. An adaptive technology of selecting block sizes for motion compensation will allow to select large blocks for homogeneous areas of the frame, and smaller blocks for images with complex motion. The proposed method can effectively eliminate temporary redundancy and increase the compression ratio of video frames with minimal computational resources. The results of modeling and evaluating the effectiveness of the developed algorithm are presented.

关键词： Motion compensation Redundancy Encoding Video compression Video coding Image coding compression algorithms

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DNA compression using an innovative Index based Coding Algorithm

DNA Compression using an innovative Index based Coding Algor...

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IEEE International Conference on Multi Topic

作者： Shan E Zahra Khalid Masood Muhammad Asif Computer Science Lahore Garrison University Lahore Pakistan

ISBN: (数字)9781728140018

ISBN: (纸本)9781728140025

Biological data mainly comprises of Deoxyribonucleic acid (DNA) and protein sequences. These are the biomolecules, which are present in all the cells of human beings. DNA Data is so huge that it requires enormous space to store the data for a single person. Even with cloud computing, storage of DNA data is a major issue as this data consists of long chain of DNA base pair sequential combinations. DNA and protein sequence databases take hundreds of gigabyte (GB) storage space. Thus data compression in genomics is a very important and challenging task. To reduce the size of DNA, we have designed an innovative technique that employs the Run length Index based Coding (RLIBC) algorithm that encrypts DNA samples and reduces its size significantly. The proposed Technique RLIBC has been compared with all the relevant techniques and it is found that it has best compression ratio and less complexity.

关键词： DNA Indexes Encoding Genomics Bioinformatics compression algorithms

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SPDP: An Automatically Synthesized Lossless compression Algorithm for Floating-Point Data

SPDP: An Automatically Synthesized Lossless Compression Algo...

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Data compression Conference (DCC)

作者： Claggett, Steven Azimi, Sahar Burtscher, Martin Texas State Univ Dept Comp Sci San Marcos TX 78666 USA

ISBN: (纸本)9781538648834

Scientific computing produces, transfers, and stores massive amounts of single- and double-precision floating-point data, making this a domain that can greatly benefit from data compression. To gain insight into what makes an effective lossless compression algorithm for such data, we generated over nine million algorithms and selected the one that yields the highest compression ratio on 26 datasets. The resulting algorithm, called SPDP, comprises four data transformations that operate exclusively at word or byte granularity. Nevertheless, SPDP delivers the highest compression ratio on eleven datasets and, on average, outperforms all but one of the seven compared compressors. An analysis of SPDP's internals reveals how to build effective compression algorithms for scientific data.

关键词： compression algorithms Compressors Approximation algorithms Transforms Image coding Scientific computing Filtering algorithms

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Comparative Study of Performances in Lossless Data compression for English and Romanian Text Files Using the Q-Coder

Comparative Study of Performances in Lossless Data Compressi...

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International Symposium on Fundamentals of Electrical Engineering (ISFEE)

作者： Radescu, Radu Univ Politehn Bucuresti Fac Elect Telecommun & Informat Technol Appl Elect & Informat Engn Dept 1-3 Iuliu Maniu Blvd RO-061071 Bucharest Romania

ISBN: (纸本)9781538672129

In order to achieve the best and most relevant performance in the field of lossless data compression, but also in order to deepen and refine the results obtained by the type of data to which the compression and decompression operation is applied, this work focuses on compression using the Q-coder, which is a relatively new and less-used coder than the QM-coder, which largely uses the same principles, except that the QM -coder is better known, being mainly used in the JPEG standard. Based on coding and decoding principles using the Q-Coder, its compression performances are compared with other similar compression methods, techniques and algorithms by applying compression to text files in both English and Romanian languages but also on other types of data (images) that allow efficient storage of information in the memory of desktop, mobile or portable computing systems. The experimental results obtained for the compression performance differ significantly depending on the inner characteristics and statistical particularities of each studied natural language. The article interprets these comparative tests and highlights the subsequent differences in compression performance, providing useful conclusions and recommendations, which can be extended to texts from different other natural languages.

关键词： Data compression Source coding compression algorithms Adaptive coding Text processing Lossless methods

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An Optimization Method of WebP Images Lossy compression Algorithm for FPGAs

An Optimization Method of WebP Images Lossy Compression Algo...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Yaqian Zhao Zhenhua Guo Baoyu Fan Kai Gao Li Wang Fang Cao Inspur Electronic Information Industry Co. Ltd. Jinan China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

To improve the efficiency of WebP images lossy compression algorithm for heterogeneous accelerating based on FPGAs in data center server, this paper proposed an optimization method of WebP image lossy compression algorithm for FPGAs. By adopting the optimization method of this paper, the overall throughput performance of WebP heterogeneous acceleration solution based on OpenCL language can be up to 281MPixel/s. The energy efficiency ratio is 2.29x higher than Intel Xeon E5-2690v3 processor. Compare with the industry-leading WebP heterogeneous acceleration solution of Xilinx and CTAccel, the throughput performance of this paper is 2.5x better than Xilinx and 1.8x better than CTAccel. Finally, this paper improves the utilization of RAM resources according to the characteristics of the RAM block in the FPGA.

关键词： Field programmable gate arrays compression algorithms Image coding Pipeline processing Quantization (signal) Acceleration Transforms

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Light Field Image compression with Random Access

Light Field Image Compression with Random Access

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Data compression Conference (DCC)

作者： Hadi Amirpour Antonio Pinheiro Manuela Pereira Fernando J.P. Lopes Mohammad Ghanbari Instituto de Telecomunicacoes and Universidade da Beira Interior Covilha Portugal Instituto de Telecomunicacoes and Polytechnic Institute of Coimbra - ISEC Portugal University of Tehran Tehran Iran

In light field compression, besides coding efficiency, providing random access to individual views is also a very significant factor. Highly efficient compression methods usually lack random access. Similarly, random access methods usually reduce the compression efficiency. To address this trade-off, a light field image encoding method is proposed in this paper which favors random access. In the proposed scheme 15×15 view images are divided into 25 independent 3×3 view images which are called Macro View Image (MVI). To encode MVIs, the central view image is used to compress its immediate neighboring view images using a hierarchical reference structure. To encode the central view of each MVI, the most central view image, along with the center of at most three MVIs, are used as the reference images for the disparity estimation. In addition, the proposed method enables the use of parallel computation to improve encoding/decoding time complexity. To reduce memory footprint in case a Region of Interest (ROI) is required, HEVC tile partitioning is used.

关键词： Image coding Data compression Rate-distortion Computer science compression algorithms Rendering (computer graphics) Decoding

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