Open AccessProceedings Article
Image Compression Using Neural Network
Sangeeta Mishra,Sudhir Savarkar +1 more
- 03 Oct 2012
- Iss: 8
TL;DR: Apart from the existing technology on image compression represented by series of JPEG, MPEG and H.26x standards, new technology such as neural networks and genetic algorithms are being developed to explore the future of image coding.
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Abstract: Apart from the existing technology on image compression represented by series of JPEG, MPEG and H.26x standards, new technology such as neural networks and genetic algorithms are being developed to explore the future of image coding. Successful applications of neural networks to basic propagation algorithm have now become well established and other aspects of neural network involvement in this technology.
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Citations
•Proceedings Article
Joint autoregressive and hierarchical priors for learned image compression
David Minnen,Johannes Ballé,George Toderici +2 more
- 03 Dec 2018
TL;DR: In this article, the authors compare the performance of autoregressive, hierarchical, and combined priors in the context of image compression and find that in terms of compression performance, autoregression and hierarchical priors are complementary and can be combined to exploit the probabilistic structure in the latents better than all previous learned models.
Deep Implicit Volume Compression
Danhang Tang,Saurabh Singh,Philip A. Chou,Christian Häne,Mingsong Dou,Sean Fanello,Jonathan Taylor,Philip Davidson,Onur G. Guleryuz,Yinda Zhang,Shahram Izadi,Andrea Tagliasacchi,Sofien Bouaziz,Cem Keskin +13 more
- 14 Jun 2020
TL;DR: A novel approach for compressing truncated signed distance fields stored in 3D voxel grids, and their corresponding textures, using a block-based neural network architecture trained end-to-end, achieving state-of-the-art rate-distortion trade-off.
Multi-Layer Perceptron Neural Network and nearest neighbor approaches for indoor localization
Mustapha Dakkak,Boubaker Daachi,Amir Nakib,Patrick Siarry +3 more
- 04 Dec 2014
TL;DR: A new metric is proposed to enhance the performance of the KNN method, called d-nearest neighbor, and the results show the efficiency of the proposed enhancement in the case of a heterogeneous high resolution database.
15
ANNIE-Artificial Neural Network-based Image Encoder
TL;DR: A technical system is developed that incorporates a priori information on typical image contents in image compression on the basis of artificial neural networks and thus increases compression performance for larger image data sets with frequently recurring image contents.
15
•Posted Content
Hybrid Approaches to Image Coding: A Review
Rehna. V. J,Jeyakumar. M. K +1 more
TL;DR: In this article, different hybrid approaches to image compression are discussed, in which combining two or more traditional approaches to enhance the individual methods and achieve better-quality reconstructed images with higher compression ratio.
6
References
•Book
Computer Architecture: A Quantitative Approach
John L. Hennessy,David A. Patterson +1 more
- 01 Dec 1989
TL;DR: This best-selling title, considered for over a decade to be essential reading for every serious student and practitioner of computer design, has been updated throughout to address the most important trends facing computer designers today.
12.6K
Multiplexer-based array multipliers
TL;DR: In this article, the synchronous computation of the partial sums of the two operands is proposed for the parallel multiplication of two n-bit numbers, which permits an efficient realization of parallel multiplication using iterative arrays.
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A Quantitative Approach
Robert G. Shackleton
- 01 Jan 2005
TL;DR: This article applied quantitative techniques such as linguistic distance, cluster analysis, principal components analysis, and regression analysis to data on English speech variants in England and America to distinguish clusters of speakers with similar speech patterns, and isolate groups of variants that distinguish those groups of speakers.
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