Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Sebastia Mijares i Verdu"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12169-12180 (2024)
Fixed-quality image compression is a coding paradigm where the tolerated introduced distortion is set by the user. This article proposes a novel fixed-quality compression method for remote sensing images. It is based on a neural architecture we have
Externí odkaz:
https://doaj.org/article/93c987e6c898476b84ad05f49d475b36
Autor:
Sebastia Mijares i Verdu, Johannes Balle, Valero Laparra, Joan Bartrina Rapesta, Miguel Hernandez-Cabronero, Joan Serra-Sagrista
Publikováno v:
2022 Data Compression Conference (DCC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::df57baec4ff5a68e26150286d969d57e
https://doi.org/10.1109/dcc52660.2022.00087
https://doi.org/10.1109/dcc52660.2022.00087
A Scalable Reduced-Complexity Compression of Hyperspectral Remote Sensing Images Using Deep Learning
Autor:
Sebastià Mijares i Verdú, Johannes Ballé, Valero Laparra, Joan Bartrina-Rapesta, Miguel Hernández-Cabronero, Joan Serra-Sagristà
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4422 (2023)
Two key hurdles to the adoption of Machine Learning (ML) techniques in hyperspectral data compression are computational complexity and scalability for large numbers of bands. These are due to the limited computing capacity available in remote sensing
Externí odkaz:
https://doaj.org/article/c02e616a385d421491d0eb22c29ec1e1