中国科学院机构知识库网格系统: 检索

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	Bifurcated Backbone Strategy for RGB-D Salient Object Detection 期刊论文 OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 8727-8742 作者: Zhai, Yingjie; Fan, Deng-Ping; Yang, Jufeng; Borji, Ali; Shao, Ling \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2021/12/28 RGB-D salient object detection bifurcated backbone strategy multi-level features cascaded refinement
	Using multi-level fusion of local features for land-use scene classification with high spatial resolution images in urban coastal zones 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2018, 卷号: 70, 页码: 1-12 作者: Lu, Chen; Yang, Xiaomei; Wang, Zhihua; Li, Zhi \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2019/05/23 Land-use scene classification Local features fusion Multi-level Urban coastal zones
	Using multi-level fusion of local features for land-use scene classification with high spatial resolution images in urban coastal zones 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2018, 卷号: 70, 页码: 1-12 作者: Lu, Chen; Yang, Xiaomei; Wang, Zhihua; Li, Zhi \| 收藏 \| 浏览/下载：17/0 \| 提交时间：2019/05/23 Land-use scene classification Local features fusion Multi-level Urban coastal zones
	Using multi-level fusion of local features for land-use scene classification with high spatial resolution images in urban coastal zones 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2018, 卷号: 70, 页码: 1-12 作者: Lu, Chen; Yang, Xiaomei; Wang, Zhihua; Li, Zhi \| 收藏 \| 浏览/下载：18/0 \| 提交时间：2019/05/23 Land-use scene classification Local features fusion Multi-level Urban coastal zones
	Multi-Scale Blobs for Saliency Detection in Satellite Images SCI/SSCI论文 OAI收割 2016 作者: Zhou Y. N.; Luo, J. C.; Hu, X. D.; Shen, Z. F.; Yu, GR 收藏 \| 浏览/下载：24/0 \| 提交时间：2016/12/16 Multi-scale blob Multi-level distance transform Salient region Object center Satellite image remote-sensing images features scale
	面向第二语言学习的作文自动评估技术学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2012 作者: 彭星源收藏 \| 浏览/下载：140/0 \| 提交时间：2015/09/02 作文自动评估主题内容一致分析潜在语义分析词汇评分多层面文本特征有限状态转换 automated essay assessment topic content consistent analysis latent semantic analysis word score multi-level text features finite state transducer
	Using bidirectional binary particle swarm optimization for feature selection in feature-level fusion recognition system (EI CONFERENCE) 会议论文 OAI收割 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, May 25, 2009 - May 27, 2009, Xi'an, China 作者: Wang D.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 In feature-level fusion recognition system the other is optimizing system sensor design to get outstanding cost performance. So feature selection become usually necessary to reduce dimensionality of the combination of multi-sensor features and improve system performance in system design. In general there are two main missions. One is improving the recognition correct rate as soon as possible the optimization is usually applied to feature selection because of its computational feasibility and validity. For further improving recognition accuracy and reducing selected feature dimensions this paper presents a more rational and accurate optimization Bidirectional Binary Particle Swarm Optimization (BBPSO) algorithm for feature selection in feature-level fusion target recognition system. In addition we introduce a new evaluating function as criterion function in BBPSO feature selection method. At the last we utilized Leave-One-Out method to validate the proposed method. The experiment results show that the proposed algorithm improves classification accuracy by two percentage points while the selected feature dimensions are less one dimension than original Particle Swarm Optimization approach with 16 original feature dimensions. 2009 IEEE.