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Summary & Details

Improvement of Object Detection Training Method

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Format: PDF

Price: Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880

Publication code: 20219002

Paper/Info type: Other International Conferences

Pages: 1-1(Total 1 p)

Date of publication: Sep 2021

Publisher: JSAE

Language: English

Detailed Information

Author(E)	1) Chi-Shen Chao, 2) Mohd Hafiz Hilman Mohammad Sofian, 3) Toshio Ito
Affiliation(E)	1) Shibaura Institute of Technology, 2) Shibaura Institute of Technology, 3) Shibaura Institute of Technology
Abstract(E)	One-stage object detection shows high performance in the field of real-time object detection. Thanks to CNN, we can start to build a high accuracy object detection model. However, due to the working principle of object detection, the quality of the input image and the annotation will affect model accuracy massively. During the training process, the missed annotation in single image might confuse our model. In this paper, we designed two patterns of training method. The first pattern is making multiple annotations in single image. In the second pattern, we only annotate one object in single image and ignore others existed objects in the same image. Finally, we compared the results and check how this problem will affect the final accuracy.

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