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题名: A Visual Attention based Convolutional Neural Network for Image Classification
作者: Chen Yaran1; Zhao Dongbin1; Lv Le(吕乐)1; Li Chengdong2
出版日期: 2016-09
会议名称: The 2016 World Congress on Intelligent Control and Automation
会议日期: 12-15 June 2016
会议地点: Guilin, China
DOI: 10.1109/WCICA.2016.7578651
英文摘要: This paper presents a visual attention based convolutional neural network (CNN) to solve the image classification problem in the real complex world scene. The presented method can simulate the process of recognizing objects and find the area of interest which is related with the task. Compared with the CNN method in image classification, the model is proficient in fine-grained classification problem and has a better robustness due to its mechanism of multi-glance and visual attention. We evaluate the model on vehicle dataset, where its performance exceeds CNN baseline on image classification.
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内容类型: 会议论文
URI标识: http://ir.ia.ac.cn/handle/173211/14478
Appears in Collections:复杂系统管理与控制国家重点实验室_智能化团队_会议论文

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作者单位: 1.he State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2.he School of Information and Electrical Engineer- ing, Shandong Jianzhu University, Jinan 250101, China (

Recommended Citation:
Chen Yaran,Zhao Dongbin,Lv Le,et al. A Visual Attention based Convolutional Neural Network for Image Classification[C]. 见:The 2016 World Congress on Intelligent Control and Automation. Guilin, China. 12-15 June 2016.
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