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检索条件"任意字段=IEEE Data Compression Conference"

共 16774 条记录，以下是611-620 订阅

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SortComp (Sort-and-Compress) - Towards a Universal Lossless compression Scheme for Matrix and Tabular data

SortComp (Sort-and-Compress) - Towards a Universal Lossless ...

引用

data compression conference (DCC)

作者： Cheng, Xizhe Lin, Sian-Jheng Sun, Jie Huawei Technol Co Ltd Hong Kong R&D Ctr Hong Kong Peoples R China

ISBN: (纸本)9781665478939

A universal scheme is proposed for the lossless compression of two-dimensional tables and matrices. Instead of standard row- or column-based compression, we propose to sort each column first and record both the sorted table and the corresponding permutation table of the sorting permutations. These two tables are then separately compressed. In this new scheme, both intra- and inter-column correlations can be efficiently captured, giving rise to improved compression ratio in particular when both column-wise and row-wise dependencies cooccur. This scheme reduces the problem of the compression of an arbitrary two-dimensional table to that of a 'permutation table' together with a 'sorted table', where the former is only dependent on the table dimension and the latter can be effectively compressed column-by-column using predictive methods. Based on this scheme, a new algorithm is proposed, SortComp (sort-and-compress). For correlated columns, we give an estimation of the asymptotic bit rate of the algorithm and compare it to column-oriented compression schemes. Numerical experiments on real-life csv datasets validate the advantages of SortComp compared to existing row- and column-oriented compression algorithms.

关键词： Correlation Bit rate Estimation data compression Prediction algorithms Standards compression algorithms

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ProgDTD: Progressive Learned Image compression with Double-Tail-Drop Training

ProgDTD: Progressive Learned Image Compression with Double-T...

引用

2023 ieee/CVF conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Hojjat, Ali Haberer, Janek Landsiedel, Olaf Kiel University Germany Chalmers University of Technology Sweden

ISBN: (纸本)9798350302493

Progressive compression allows images to start loading as low-resolution versions, becoming clearer as more data is received. This increases user experience when, for example, network connections are slow. Today, most approaches for image compression, both classical and learned ones, are designed to be non-progressive. This paper introduces ProgDTD, a training method that transforms learned, non-progressive image compression approaches into progressive ones. The design of ProgDTD is based on the observation that the information stored within the bottleneck of a compression model commonly varies in importance. To create a progressive compression model, ProgDTD modifies the training steps to enforce the model to store the data in the bottleneck sorted by priority. We achieve progressive compression by transmitting the data in order of its sorted index. ProgDTD is designed for CNN-based learned image compression models, does not need additional parameters, and has a customizable range of progressiveness. For evaluation, we apply ProgDTD to the hyperprior model, one of the most common structures in learned image compression. Our experimental results show that ProgDTD performs comparably to its non-progressive counterparts and other state-of-the-art progressive models in terms of MS-SSIM and accuracy. © 2023 ieee.

关键词： Image compression

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Optimized AES for Low Power Devices 10

Optimized AES for Low Power Devices

引用

10th International conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Sarmila, K.B. Kaarthikeyan, A.R. Kaasiprasanth, A. Sri Eshwar College of Engineering Department of Computer Science and Engineering Tamil Nadu India

ISBN: (纸本)9798350384369

The Advanced Encryption Standard (AES)'s computational speed and flexibility for systems with limited resources are both greatly improved by the unique methodologies introduced in this work. We speed up encryption without compromising security by using bit manipulation techniques for shifting rows and mixing column procedures. Furthermore, to overcome the limitations of fixed key length (128, 192, or 256 bit - length), we suggest an adaptive key size strategy that is adapted to data transfer needs and desired security levels. We recommend incorporating data compression methods as a preprocessing step to further increase efficiency by significantly lowering data size and computing effort. We show how data compression can make it possible to use smaller 64-bit keys in applications like WiFi devices, improving both performance and security. Further simplifying AES procedures is encouraged by our recommendation to swap memory-intensive matrices out for more effective data structures. This comprehensive strategy helps AES meet the requirements of a wide range of resource-constrained applications while also speeding up encryption and decryption procedures. © 2024 ieee.

关键词： data compression

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Characterization and Detection of Artifacts for Error-controlled Lossy Compressors 30

Characterization and Detection of Artifacts for Error-contro...

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30th International conference on High Performance Computing, data, and Analytics (HiPC)

作者： Jiao, Pu Di, Sheng Liu, Jinyang Liang, Xin Cappello, Franck Univ Kentucky Lexington KY USA Univ Calif Riverside Riverside CA 92521 USA Argonne Natl Lab Lemont IL USA

ISBN: (纸本)9798350383225

Today's scientific high-performance computing (HPC) applications are often running on large-scale environments, producing extremely large volumes of data that need to be compressed effectively for efficient storage or data transfer. Error-bounded lossy compression is arguably the most efficient way to this end, because it can get very high compression ratios while controlling the data distortion strictly based on user requirements for compression errors. However, error-bounded lossy compressors may have serious artifact issues in situations with relatively large error bound or high compression ratios, which is highly undesirable to users. In this paper, we comprehensively characterize the artifacts for multiple state-of-the-art error-bounded lossy compressors (including SZ-1.4, SZ-2.1, SZ-3.0, FPZIP, ZFP, MGARD) and provide an in-depth analysis for the root cause of these artifacts. We summarize the artifact issue into three types and also develop an efficient artifact detection algorithm for each type of artifact. We finally evaluate our artifact detection methods using four scientific datasets, which demonstrates that the proposed methods are able to detect artifact issues under linear time complexity.

关键词： High-performance computing scientific data lossy compression compression artifacts

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Distributed Filter Based on SICI data compression over Sensor Networks 35

Distributed Filter Based on SICI Data Compression over Senso...

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35th Chinese Control and Decision conference (CCDC)

作者： Shen, Yuqing Sun, Shuli Heilongjiang Univ Sch Elect Engn Harbin Peoples R China

ISBN: (纸本)9798350334722

The distributed filtering problem based on data compression is studied for linear discrete time-varying systems over sensor networks. At each sensor node, sequential inverse covariance intersection (SICI) fusion algorithm is used to compress the estimates received from neighbor nodes. A distributed recursive filter is presented based on compressed data. The filtering gain (FG) and consensus gain (CG) are solved by locally minimizing an upper bound of the filtering error covariance matrix (FECM). It avoids the calculation of cross-covariance matrices (CCMs) and reduces the computational burden. Simulation results verify the effectiveness of the algorithm.

关键词： sensor network distributed recursive filter SICI fusion data compression upper bound of FECM

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Joint compression and Demosaicking For Satellite Images 48

Joint Compression and Demosaicking For Satellite Images

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48th ieee International conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Bacchus, Pascal Fraisse, Renaud Roumy, Aline Guillemot, Christine Inria Rennes France Airbus Defence and Space Toulouse France

ISBN: (纸本)9781728163277

Image sensors used in real camera systems are equipped with colour filter arrays which sample the light rays in different spectral bands. Each colour channel can thus be obtained sep-arately by considering the corresponding colour filter. While existing compression solutions mostly assume that the captured raw data has been demosaicked prior to compression, in this paper, we describe an end-to-end trainable neural network for joint compression and demosaicking of satellite images. We first introduce a training loss combining a perceptual loss with the classical mean square error, which is shown to better preserve the high-frequency details present in satellite images. We then present a multi-loss balancing strategy which significantly improves the performance of the proposed joint demosaicking-compression solution. © 2023 ieee.

关键词： Deep Image compression Demosaicking Neural Networks

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Customizing Synthetic data for data-Free Student Learning

Customizing Synthetic Data for Data-Free Student Learning

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ieee International conference on Multimedia and Expo (ICME)

作者： Luo, Shiya Chen, Defang Wang, Can Zhejiang Univ Hangzhou Peoples R China ZJU Bangsun Joint Res Ctr Hangzhou Peoples R China Zhejiang Univ Shanghai Inst Adv Study Hangzhou Peoples R China

ISBN: (纸本)9781665468916

data-free knowledge distillation (DFKD) aims to obtain a lightweight student model without original training data. Existing works generally synthesize data from the pre-trained teacher model to replace the original training data for student learning. To more effectively train the student model, the synthetic data shall be customized to the current student learning ability. However, this is ignored in the existing DFKD methods and thus negatively affects the student training. To address this issue, we propose Customizing Synthetic data for data-Free Student Learning (CSD) in this paper, which achieves adaptive data synthesis using a self-supervised augmented auxiliary task to estimate the student learning ability. That is, data synthesis is dynamically adjusted to enlarge the cross entropy between the labels and the predictions from the self-supervised augmented task, thus generating the hard samples for the student model. The experiments on various datasets and teacher-student models show the effectiveness of our proposed method. Code is available at: https://***/luoshiya/CSD

关键词： data-free knowledge distillation self-supervision model compression

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Efficient Decoder for Learned Image compression via Structured Pruning

Efficient Decoder for Learned Image Compression via Structur...

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data compression conference (DCC)

作者： Liao, Liewen Li, Shaohui Luo, Jixiang Dai, Wenrui Li, Chenglin Zou, Junni Xiong, Hongkai Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9781665478939

We propose a structured pruning method to achieve a light-weighted decoder of learned image compression to accommodate various terminals. The structured pruning method identifies the effectiveness of each channel of decoder via gradient ascent and gradient descent while maintaining the encoder and entropy model. To our best knowledge, this paper is the first attempt to design a structured pruning method for universal pretrained learned image compression. Experimental results demonstrate that the proposed method can reduce about 40% parameters and save 25% inference time at the cost of 0.23 dB BD-PSNR and 4.33% BD-rate change.

关键词： Image coding Costs data compression Entropy Decoding

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Periscope: A Framework for Visualizations of Multiresolution Spatiotemporal data at Scale

Periscope: A Framework for Visualizations of Multiresolution...

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2024 ieee International conference on Big data, Bigdata 2024

作者： Lewark, Everett Young, Matthew Khandelwal, Paahuni Pallickara, Sangmi Lee Pallickara, Shrideep Colorado State University Department of Computer Science Fort CollinsCO United States

ISBN: (纸本)9798350362480

The crux of this study is to support browser-based visualizations of spatiotemporally evolving phenomena. Such phenomena arise in myriad domains spanning terrestrial, oceanic, and atmospheric processes. The data are voluminous, have diverse representational formats and projection systems, and are multivariate. We rely on a novel mix of tiling, caching, compression, perceptual limits, speculative prefetching, and dynamic generation of tiles. Our refinements at the client and server-side work in concert with each other to leverage client-side resources, minimize duplicate processing, and effective prefetching to ensure interactive explorations at scale. Our benchmarks profiled several aspects of our methodology and demonstrate the suitability of our refinements. © 2024 ieee.

关键词： Visualization

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Efficiency Estimation of Video compression with a Bidirectional TV Images Resizing 25

Efficiency Estimation of Video Compression with a Bidirectio...

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25th ieee International conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Akhmedova, Anora Kh. Gavrilov, Igor A. Puziy, Anastasia N. Gubenko, Vladislav A. Radik, Alkhamov R. Dept. of Television and Radio Broadcasting Systems TUIT named after Muhammad Al-Khwarizmi Tashkent city Uzbekistan Dept. of Applied Mathematics and Informatics Tashkent branch of Moscow State University named after M. Lomonosov Tashkent city Uzbekistan

ISBN: (纸本)9798350389234

The possibility of using wavelet transformations for bidirectional resize (scaling) of TV images is considered in the article. It is preliminary twice reduction of image sizes before compression and restoration of their sizes after decoding. This approach makes it possible to reduce the image data before encoding by a factor of 4 and thereby increase the efficiency of video streams encoding of broadcast and industrial TV, especially in 4K and 8K formats. But since wavelet transforms do not reduce the volume of video data inside a frame, in the article. the possibility of zeroing the array of HF (high frequency) wavelet coefficients is investigated and its impact on the visual quality of test images of various structures and scenes is assessed. It was found that direct display of low frequency coefficients in the form of pixel values leads to the appearance of point color distortions, since they can have negative values. Therefore, ways to eliminate negative values in the array of low-frequency coefficients are considered. An assessment of the efficiency increasing of video compression by using the image scaler in a wavelet video codec Dirac are presented. © 2024 ieee.

关键词： Image compression

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