Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives
نویسندگان
چکیده
منابع مشابه
Deep Unsupervised Domain Adaptation for Image Classification via Low Rank Representation Learning
Domain adaptation is a powerful technique given a wide amount of labeled data from similar attributes in different domains. In real-world applications, there is a huge number of data but almost more of them are unlabeled. It is effective in image classification where it is expensive and time-consuming to obtain adequate label data. We propose a novel method named DALRRL, which consists of deep ...
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1. Loss Function Derivative In this section we outline the derivative of Equation 8 for the backpropagation algorithm; min U J = L(Us) + γM(Us, Ut) + ηH(Us, Ut), (8) where, U := {Us ∪ Ut} and (γ, η) control the importance of domain adaptation (1) and target entropy loss (7) respectively. In the following subsections, we outline the derivative of the individual terms w.r.t. the input U. 1.1. Der...
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ژورنال
عنوان ژورنال: APSIPA transactions on signal and information processing
سال: 2022
ISSN: ['2048-7703']
DOI: https://doi.org/10.1561/116.00000192