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检索条件"主题词=Compression algorithms"

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compression of Activation Signals from Split Deep Neural Network

Compression of Activation Signals from Split Deep Neural Net...

引用

IEEE Latin-American Conference on Communications, LATINCOM

作者： Flávio Brito Lucas Silva Leonardo Ramalho Silvia Lins Neiva Linder Aldebaro Klautau Lund University Lund Sweden Ericsson Research Stockholm Sweden LASSE - 5G & IoT Research Group Federal University of Pará Belém Brazil Ericsson Research Indaiatuba Brazil

The use of artificial neural networks for the purpose of image classification, together with the advancement in computational capabilities of edge devices, plays an important role in the new emerging 5G use case scenarios. However, one of the main challenges of applications involving the use of these networks in edge devices is still the limitation of computational resources. An alternative for saving resources and promoting privacy are the split learning (or split inference) techniques, in which a deep neural network is cut into two parts and executed in distinct devices. Most of these techniques rely on sending the activation signals (output of the cut layer) through the communication channel. This work proposes a new compression algorithm for decreasing the bit rate required for the transmission of the activation signals (or simply “scores”). The presented results demonstrate that the transmission rate can be decreased without hurting the neural network accuracy.

关键词： Deep learning Privacy Image edge detection Propagation losses Sparse matrices Servers compression algorithms

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A low-power area-efficient design and comparative analysis for high-resolution neural data compression

A low-power area-efficient design and comparative analysis f...

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International Conference on Microelectronics, ICM

作者： Mohammed Ashraf Hassan Mostafa Ahmed A. El-Adawy Electronics and Communications Engineering Department Cairo Universitv Giza Egypt Center for Nanoelectronics and Devices AUC and Zewail City of Science and Technology New Cairo Egypt

Nowadays, brain scientific research progress depends on signal compression at high spatial resolutions, for efficient storage and low-rate transmission through wireless connection to outside world. So that neural data compression at the implant site is necessary in order to conform with the wireless rates restrictions. In this paper, the high spatial correlation is utilized to increase the data compression ratio. Then we investigate and compare three different proposed low-power image compression algorithms based on discrete cosine transform (DCT) and discrete wavelet transform (DWT) to provide the best trade-off between hardware complexity and compression performance. Hence, we conclude that Adaptive 2D-DWT algorithm is a promising solution for low-power implantable devices.

关键词： Discrete wavelet transforms compression algorithms Hardware Quantization (signal) Correlation Discrete cosine transforms Spatial resolution

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SPECTRUM analysis of multispectral imagery in conjunction with wavelet/KLT data compression

SPECTRUM analysis of multispectral imagery in conjunction wi...

引用

Asilomar Conference on Signals, Systems & Computers

作者： J.N. Bradley C.M. Brislawn Los Alamos National Laboratory Los Alamos NM USA

The data analysis program, SPECTRUM, is used for fusion, visualization, and classification of multispectral imagery. To facilitate data transmission and storage, a compression algorithm is proposed based on spatial wavelet transform coding and KLT decomposition of interchannel spectral vectors, followed by adaptive optimal multiband scalar quantization. The performance of SPECTRUM clustering and visualization is evaluated on compressed multispectral data. 8-bit visualizations of 56-bit data show little visible distortion, at 50:1 compression and graceful degradation at higher compression ratios.< >

关键词： Image analysis Multispectral imaging Data visualization Data analysis Data communication compression algorithms Transform coding Karhunen-Loeve transforms Quantization Image coding

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Construction of synthetic test signals for evaluation lossy compression methods for measurement signals

Construction of synthetic test signals for evaluation lossy ...

引用

IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： W. Gawedzki Department of Measurement and Instrumentation AGH University of Science and Technology Krakow Poland

The problems of measurement signal compression recorded under long-term monitoring conditions are presented in the paper. The functional quality of lossy compression algorithms in metrological applications depends strongly on the data stream dynamic properties. This was the reason for presenting a proposal to use synthetic test signals for investigating and classification compression algorithms. Application of such signals to study the lossy compression algorithms makes the results obtained this way independent of the shape of an individual signal and makes them obligatory for the whole class of measurement signals. By changing parameters of synthetic signals, the functioning of algorithms can be investigated within certain intervals of parameter values, and not, as it is for real signals, for single values of these parameters. A method for generating synthetic test signals for testing metrological properties of lossy compression methods allowing unification of the obtained results is presented in the paper. The results of exemplary simulation experiments are presented.

关键词： Testing Loss measurement Signal processing algorithms compression algorithms Shape measurement Signal processing Instruments Condition monitoring Proposals Signal generators

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A High-Throughput Hardware Accelerator for Lempel-Ziv 4 compression Algorithm

A High-Throughput Hardware Accelerator for Lempel-Ziv 4 Comp...

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IEEE Workshop on Signal Processing Systems (SIPS)

作者： Tao Chen Suwen Song Zhongfeng Wang School of Electronic Science and Engineering Nanjing University Nanjing China School of Integrated Circuits Sun Yat-sen University Shenzhen China

ISBN: (数字)9798350373752

ISBN: (纸本)9798350373769

This paper delves into recent hardware implementations of the Lempel-Ziv 4 (LZ4) algorithm, highlighting two key factors that limit the throughput of single-kernel compressors. Firstly, the actual parallelism exhibited in single-kernel designs falls short of the theoretical potential. Secondly, the clock frequency is constrained due to the presence of the feedback loops. To tackle these challenges, we propose a novel scheme that restricts each parallelization window to a single match, thus elevating the level of actual parallelism. Furthermore, by restricting the maximum match length, we eliminate the feedback loops within the architecture, enabling a significant boost in throughput. Finally, we present a high-speed hardware architecture. The implementation results demonstrate that the proposed architecture achieves a throughput of up to 16.10 Gb/s, exhibiting a 2.648× improvement over the start-of-the-art. The new design only results in an acceptable compression ratio reduction ranging from 4.93% to 11.68% with various numbers of hash table entries, compared to the LZ4 compression ratio achieved by official software implementations disclosed on GitHub.

关键词： Feedback loop Computer architecture Parallel processing Signal processing Throughput Software Parallel architectures compression algorithms Hardware acceleration Software development management

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Optimal refinement/significance map tradeoffs in SPIHT-based image compression

Optimal refinement/significance map tradeoffs in SPIHT-based...

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Asilomar Conference on Signals, Systems & Computers

作者： C.D. Creusere Klipsch School of Electrical and Computer Engineering New Mexico State University USA

ISBN: (纸本)0780365143

A rate-distortion-optimal embedded image compression algorithm is one in which each bit is generated by the encoder in such a way that the reconstruction error of the decoded image is reduced as much as possible when that bit is received. Popular embedded algorithms like set partitioning in hierarchical trees (SPIHT) use heuristic techniques to approximately achieve such optimality. Two other approaches have been developed recently that are rigorously optimized for rate-distortion within their respective algorithmic frameworks. In this work, we address the question of optimality within the framework of SPIHT, focusing specifically on the ordering of refinement and significance map information within the bit stream. From our experimental results, we conclude that SPIHT is almost optimal with respect to its ordering of these passes.

关键词： Image coding Decoding Rate-distortion Wavelet transforms Streaming media Image reconstruction Partitioning algorithms compression algorithms Computational complexity Bit rate

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compression of hyperspectral images with 2D wavelet transform using adjacent information and SPIHT slgorithm

Compression of hyperspectral images with 2D wavelet transfor...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： S. Lee E. Lee H. Choi C. Lee Department Electrical and Electronic Eng Yonsei University Seoul South Korea

In this paper, we propose compression algorithms for hyperspectral images based on the wavelet transform using adjacent band information. In the proposed algorithm, we divide the spectral bands into a number of groups. Then, within each group, we select a representative spectral band which has highest correlations with the remaining spectral bands within the group. The representative image is compressed using the 2-dimensional SPIHT algorithm. A characteristic of the SPIHT algorithm is that it provides information on significant coefficients of transformed images, which have large energies. We explore this characteristic and use the information to encode adjacent band images of the representative image.

关键词： Image coding Hyperspectral imaging Wavelet transforms Hyperspectral sensors compression algorithms Encoding Pixel Remote sensing Sensor phenomena and characterization Sensor systems

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Selective merging-based reference frame memory compression

Selective merging-based reference frame memory compression

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： Soongi Hong Dahjung Chung Yoonsik Choe School of Electrical and Electronic Engineering Image Information Laboratory Yonsei University Seoul South Korea

Although IBDI, a coding tool that increases internal bit depth to improve compression performance for high quality video, is able to significantly improve the coding efficiency, the internal memory increment problem occurs because of the necessity of storing reference frames. Therefore, memory compression algorithm is proposed to solve the internal memory increment problem while maintaining the coding performance of IBDI. The memory compression methods have successively reduced the reference frame memory while preserving the coding efficiency by dividing a reference frame into the fixed size processing units and using additional information of each unit. However, additional information of each processing unit also has to be stored in internal frame memory; the amount of additional information could be a limitation of the effectiveness of memory compression scheme. Therefore, to relax this limitation of previous method, we propose a selective merging-based reference frame memory compression algorithm, dramatically reducing the amount of additional information. Simulation results show that the proposed algorithm provides much smaller overhead than that of the previous algorithm while keeping the coding efficiency of IBDI.

关键词： Merging Encoding Software algorithms compression algorithms Heuristic algorithms Dynamic range Software

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A lossless image compression algorithm by combining DPCM with integer wavelet transform

A lossless image compression algorithm by combining DPCM wit...

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Proceedings of the IEEE Circuits and Systems Symposium on Emerging Technologies

作者： Min Shi Shengli Xie The Research Institute of Radio & Automatic Control South China University of Technology Guangzhou Guangdong China

A lossless image compression method by combining DPCM transform with integer wavelet transform is presented in this paper. Firstly, DPCM transform is used in this compression algorithm and the difference image is transformed by integer wavelet, then we can get bit stream by lossless SPIHT algorithm. Finally, the reconstructed image is obtained by corresponding reversible transform. This method is very simple and hardware implement is also easy. The simulation results show that it is an effective lossless image compression method.

关键词： Image coding Wavelet transforms Streaming media Image reconstruction Hardware Quantization Automatic control compression algorithms Medical simulation Fingerprint recognition

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compression for 3D face recognition applications

Compression for 3D face recognition applications

引用

IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Lorenzo Granai Miroslav Hamouz Jose R. Tena Theodore Vlachos Centre for Vision Speech and Signal Processing University of Surrey Guildford UK

This paper proposes a novel 3D lossy compression algorithm tailored for 3D faces. We analyse the effects of compression on the face verification rate and measure recognition performances on the face recognition grand challenge database. Whilst preserving the spatial resolution enabling reconstruction of surface details, the proposed scheme achieves substantial compression to the extent that personal 3D biometric data could fit on a 2D barcode.

关键词： Face recognition Surface fitting Signal processing algorithms compression algorithms Face detection Performance analysis Testing Shape Humans Speech processing

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