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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Chou, Kuang-PenSubject: search.filters.subject.Deep learning

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    Deep Sparse Representation Classifier for facial recognition and detection system
    (2019-07-01)
    Cheng, Eric-Juwei
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    Chou, Kuang-Pen
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    Rajora, Shantanu
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    Jin, Bo-Hao
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    Tanveer, M.
    This paper proposes a two-layer Convolutional Neural Network (CNN) to learn the high-level features which utilizes to the face identification via sparse representation. Feature extraction plays a vital role in real-world pattern recognition and classification tasks. The details description of the given input face image, significantly improve the performance of the facial recognition system. Sparse Representation Classifier (SRC) is a popular face classifier that sparsely represents the face image by a subset of training data, which is known as insensitive to the choice of feature space. The proposed method shows the performance improvement of SRC via a precisely selected feature exactor. The experimental results show that the proposed method outperforms other methods on given datasets. (C) 2019 Elsevier B.V. All rights reserved.
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    A METHOD TO ENHANCE THE DEEP LEARNING IN AN AERIAL IMAGE
    (2017-01-01)
    Chou, Kuang-Pen
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    Li, Dong-Lin
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    Lin, Wen-Chieh
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    Prasad, Mukesh
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    Lin, Chin-Teng
    In this paper, we propose a kind of pre-processing method which can be applied to the depth learning method for the characteristics of aerial image. This method combines the color and spatial information to do the quick background filtering. In addition to increase execution speed, but also to reduce the rate of false positives