Unsupervised semantic deep hashing
نویسندگان
چکیده
منابع مشابه
Unsupervised Semantic Deep Hashing
In recent years, deep hashing methods have been proved to be efficient since it employs convolutional neural network to learn features and hashing codes simultaneously. However, these methods are mostly supervised. In real-world application, it is a time-consuming and overloaded task for annotating a large number of images. In this paper, we propose a novel unsupervised deep hashing method for ...
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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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Hashing techniques have been intensively investigated for large scale vision applications. Recent research has shown that leveraging supervised information can lead to high quality hashing. However, most existing supervised hashing methods only construct similarity-preserving hash codes. Observing that semantic structures carry complementary information, we propose the idea of cotraining for ha...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2019
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2019.01.020