Lossless Image Compression by Joint Prediction of Pixel and Context Using Duplex Neural Networks

Autor: Hochang Rhee, Yeong Il Jang, Seyun Kim, Nam Ik Cho

Publikováno v: IEEE Access, Vol 9, Pp 86632-86645 (2021)

This paper presents a new lossless image compression method based on the learning of pixel values and contexts through multilayer perceptrons (MLPs). The prediction errors and contexts obtained by MLPs are forwarded to adaptive arithmetic encoders, l

Externí odkaz: https://doaj.org/article/439ced23b8bf4d9c954bdfa4db4f39e8

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Можливість застосування методів арифметичного кодування в системах криптографічного захисту інформації

Publikováno v: Ukrainian Scientific Journal of Information Security; Vol. 26 No. 3 (2020); 156-167
Безопасность информации; Том 26 № 3 (2020); 156-167
Безпека інформації; Том 26 № 3 (2020); 156-167

The article analyzes recent publications, which pointed to the rapid creation of data by various types ofmedia. It was noted that a fifth of the data generated is critical and needs to be protected. To reduce the amount of data, it is proposed to use

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=aviationuniv::1d202f3aae6c256c14398e3b565f5f68
https://jrnl.nau.edu.ua/index.php/Infosecurity/article/view/15157

A phantom axon setup for validating models of action potential recordings

Autor: Serge Bernard, Olivier Rossel, Guy Cathébras, David Guiraud, Fabien Soulier

Publikováno v: Medical and Biological Engineering and Computing
Medical and Biological Engineering and Computing, Springer Verlag, 2016, 10 (4), pp.671-678. ⟨10.1007/s11517-016-1463-3⟩
Medical and Biological Engineering and Computing, 2016, 10 (4), pp.671-678. ⟨10.1007/s11517-016-1463-3⟩

Electrode designs and strategies for electroneurogram recordings are often tested first by computer simulations and then by animal models, but they are rarely implanted for long-term evaluation in humans. The models show that the amplitude of the pot

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa6c44aec11e72d194a0d12c89688acd
https://doi.org/10.1007/s11517-016-1463-3

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