Depth Estimation and Image Restoration by Deep Learning from Defocused Images

Autor: Nazir, Saqib, Vaquero, Lorenzo, Mucientes, Manuel, Brea, Víctor M., Coltuc, Daniela

Publikováno v: IEEE Transactions on Computational Imaging, vol. 9, pp. 607-619, 2023

Monocular depth estimation and image deblurring are two fundamental tasks in computer vision, given their crucial role in understanding 3D scenes. Performing any of them by relying on a single image is an ill-posed problem. The recent advances in the

Externí odkaz: http://arxiv.org/abs/2302.10730

A Hybrid Data-Differencing and Compression Algorithm for the Automotive Industry.

Autor: Belu, Sabin¹ (AUTHOR) sabin24@hotmail.com, Coltuc, Daniela¹ (AUTHOR) daniela.coltuc@upb.ro

Publikováno v: Entropy. May2022, Vol. 24 Issue 5, pN.PAG-N.PAG. 20p.

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Optical compressive sensing technologies for space applications: Instrumental concepts and performance analysis

Autor: Guzzi, Donatella, Coluccia, Giulio, Labate, Demetrio, Lastri, Cinzia, Magli, Enrico, Nardino, Vanni, Palombi, Lorenzo, Pippi, Ivan, Coltuc, Daniela, Barducci, Alessandro, Zuccaro Marchi, Alessandro, Raimondi, Valentina

Publikováno v: International Conference on Space Optics--ICSO 2018, Chania, Greece, 9-12/10/2018
info:cnr-pdr/source/autori:Guzzi, Donatella; Coluccia, Giulio; Labate, Demetrio; Lastri, Cinzia; Magli, Enrico; Nardino, Vanni; Palombi, Lorenzo; Pippi, Ivan; Coltuc, Daniela; Barducci, Alessandro; Zuccaro Marchi, Alessandro; Raimondi, Valentina/congresso_nome:International Conference on Space Optics--ICSO 2018/congresso_luogo:Chania, Greece/congresso_data:9-12%2F10%2F2018/anno:2018/pagina_da:/pagina_a:/intervallo_pagine

This paper presents the results of a study aimed at investigating the potential of Compressive Sensing (CS) technologies for optical space instruments. Besides assessing the pros and cons for a wide set of proposed instrumental concepts for space app

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0741074bac6f13bd6e776397d4416ea4

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