Deep Learning and Computer Vision in Remote Sensing / / Fahimeh Farahnakian, Jukka Heikkonen, Pouya Jafarzadeh, editors

• Pubblicazione: Basel : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2023
• Descrizione fisica: 1 online resource (572 pages)
• Disciplina: 621.3678
• Soggetto topico: Remote sensing
• Persona (resp. second.): JafarzadehPouya; HeikkonenJukka; FarahnakianFahimeh
• Sommario/riassunto: In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
• Titolo autorizzato: Deep Learning and Computer Vision in Remote Sensing
• ISBN: 3-0365-6369-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910683389903321
• Lo trovi qui: Univ. Federico II