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Learning Deep Relationship for Object Detection
Jul 11, 2018Author:
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Title: Learning Deep Relationship for Object Detection

Authors: Xu, N; Huo, CL

Author Full Names: Xu, Nuo; Huo, Chunlei

Source: IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, E101D (1):273-276; 10.1587/transinf.2017EDL8131 JAN 2018

Language: English

Abstract: Object detection has been a hot topic of image processing, computer vision and pattern recognition. In recent years, training a model from labeled images using machine learning technique becomes popular. However, the relationship between training samples is usually ignored by existing approaches. To address this problem, a novel approach is proposed, which trains Siamese convolutional neural network on feature pairs and finely tunes the network driven by a small amount of training samples. Since the proposed method considers not only the discriminative information between objects and background, but also the relationship between intraclass features, it outperforms the state-of-arts on real images.

ISSN: 1745-1361

IDS Number: GF2IA

Unique ID: WOS:000431760600036

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