Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MPPNB sites in the Southern Levant

Autor: Eugenio Nobile, Maurizio Troiano, Fabio Mangini, Marco Mastrogiuseppe, Jacob Vardi, Fabrizio Frezza, Cecilia Conati Barbaro, Avi Gopher

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)

Abstract This study was aimed at introducing a new method for predicting the original metrics of fragmented standardized artifacts, specifically of flint blades from the Middle Pre-Pottery Neolithic B (10,200/100–9,500/400 cal B.P.) in the Southern

Externí odkaz: https://doaj.org/article/526276858dc142f1be0d66aa5af95a3c

Prediction of Visual Quality Metrics in Lossy Image Compression

Autor: Fangfang Li, Vladimir V. Lukin, Benoit Vozel, O. Krylova, Sergey Krivenko

Publikováno v: 40th IEEE International Conference on Electronics and Nanotechnology, ELNANO 2020
40th IEEE International Conference on Electronics and Nanotechnology, ELNANO 2020, Apr 2020, Kyiv, Ukraine. pp.478-483, ⟨10.1109/ELNANO50318.2020.9088819⟩

International audience; Images of different origin are widely used nowadays in various applications including medical diagnostic systems, remote sensing, etc. Due to modern tendency to improve imaging system resolution and increase image size, it has

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1de89964c85060ed9541a3874bc3f7b
https://doi.org/10.1109/elnano50318.2020.9088819

Prediction of Quality in DCT-Based Lossy Compression of Noisy Remote Sensing Images

Autor: A. Zemliachenko, Benoit Vozel, Kacem Chehdi, Vladimir V. Lukin, Sergey K. Abramov

Publikováno v: 2017 IEEE 37th International Conference On Electronics and Nanotechnology (elnano)
2017 IEEE 37th International Conference On Electronics and Nanotechnology (elnano), Apr 2017, Kyiv, Ukraine. pp.447-450, ⟨10.1109/ELNANO.2017.7939794⟩

International audience; This paper considers specific aspects of lossy compression of noisy remote sensing images. A method based on discrete cosine transform (DCT) in 32x32 pixels blocks is analyzed. Characteristics of noise assumed additive (in ori

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::375d8e6c38715096e832e18b686b5ba8
https://univ-rennes.hal.science/hal-01622075

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