Deep Generative Models

Second MICCAI Workshop, DGM4MICCAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
1. Auflage 2022
ISBN: 978-3-031-18575-5
Verlag: Springer Nature Switzerland

Buch, Englisch, Band 13609, 127 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 224 g

Reihe: Lecture Notes in Computer Science

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Deep Generative Models, DG4MICCAI 2022, held in conjunction with MICCAI 2022, in September 2022. The workshops took place in Singapore.

DG4MICCAI 2022 accepted 12 papers from the 15 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community.

Zielgruppe

Research

Autoren/Hrsg.

Mukhopadhyay, Anirban

Oksuz, Ilkay

Yuan, Yixuan

Engelhardt, Sandy

Zhu, Dajiang

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung