Domain Adaptation in Computer Vision with Deep Learning

Edited by Hemanth Venkateswara () and Sethuraman Panchanathan ()

in Springer Books from Springer

Date: 2020
ISBN: 978-3-030-45529-3
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Chapters in this book:

Ch Chapter 1 Introduction to Domain Adaptation

Hemanth Venkateswara and Sethuraman Panchanathan

Ch Chapter 10 Adversarial Learning Approach for Open Set Domain Adaptation

Kuniaki Saito, Shohei Yamamoto, Yoshitaka Ushiku and Tatsuya Harada

Ch Chapter 11 Universal Domain Adaptation

Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang and Michael I. Jordan

Ch Chapter 12 Multi-Source Domain Adaptation by Deep CockTail Networks

Ziliang Chen and Liang Lin

Ch Chapter 13 Zero-Shot Task Transfer

Arghya Pal and Vineeth N. Balasubramanian

Ch Chapter 2 Shallow Domain Adaptation

Sanatan Sukhija and Narayanan Chatapuram Krishnan

Ch Chapter 3 d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding

Xiong Zhou, Xiang Xu, Ragav Venkatesan, Gurumurthy Swaminathan and Orchid Majumder

Ch Chapter 4 Deep Hashing Network for Unsupervised Domain Adaptation

Raghavendran Ramakrishnan, Bhadrinath Nagabandi, Jose Eusebio, Shayok Chakraborty, Hemanth Venkateswara and Sethuraman Panchanathan

Ch Chapter 5 Re-weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation

Qingchao Chen, Yang Liu, Zhaowen Wang, Ian Wassell and Kevin Chetty

Ch Chapter 6 Unsupervised Domain Adaptation with Duplex Generative Adversarial Network

Lanqing Hu, Meina Kan, Shiguang Shan and Xilin Chen

Ch Chapter 7 Domain Adaptation via Image to Image Translation

Zak Murez, Soheil Kolouri, David Kriegman, Ravi Ramamoorthi and Kyungnam Kim

Ch Chapter 8 Domain Adaptation via Image Style Transfer

Amir Atapour-Abarghouei and Toby P. Breckon

Ch Chapter 9 Towards Scalable Image Classifier Learning with Noisy Labels via Domain Adaptation

Kuang-Huei Lee, Xiaodong He, Linjun Yang and Lei Zhang

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DOI: 10.1007/978-3-030-45529-3

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