Titlebook: Synthetic Data for Deep Learning; Sergey I. Nikolenko Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license t

清晰

Adrenaline

Synthetic-to-Real Domain Adaptation and Refinement,to ensure domain adaptation, while the data remains as synthetic as it has been. We will discuss neural architectures for both approaches, including many models based on generative adversarial networks.

opprobrious

Springer Optimization and Its Applicationshttp://image.papertrans.cn/t/image/884355.jpg

失望昨天

APNEA

Sergey I. NikolenkoThe first book about synthetic data, an important field which is rapidly rising in popularity throughout machine learning.Provides a wide survey of several different fields where synthetic data is or

Licentious

978-3-030-75180-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

jet-lag

Synthetic Data for Deep Learning978-3-030-75178-4Series ISSN 1931-6828 Series E-ISSN 1931-6836

形上升才刺激

agonist

放肆的你