Inpainting and Denoising Challenges

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Escalera, Sergio (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Ayache, Stephane (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Wan, Jun (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Madadi, Meysam (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Güçlü, Umut (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Baró, Xavier (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: The Springer Series on Challenges in Machine Learning,
• Θέματα: Artificial intelligence.; Optical data processing.; Pattern recognition.; Artificial Intelligence.; Image Processing and Computer Vision.; Pattern Recognition.

The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/v...