中国科学院机构知识库网格系统: 检索

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	Improving Prediction of Self-interacting Proteins Using Stacked Sparse Auto-Encoder with PSSM profiles 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES, 2018, 卷号: 14, 期号: 8, 页码: 983-991 作者: Wang, YB (Wang, Yan-Bin); You, ZH (You, Zhu-Hong); Li, LP (Li, Li-Ping); Huang, DS (Huang, De-Shuang); Zhou, FF (Zhou, Feng-Feng) \| 收藏 \| 浏览/下载：43/0 \| 提交时间：2018/07/16 Deep Learning Zernike Moments Probabilistic Classification Vector Machines
	Accurate Prediction of ncRNA-Protein Interactions From the Integration of Sequence and Evolutionary Information 期刊论文 OAI收割 FRONTIERS IN GENETICS, 2018, 卷号: 9, 期号: 10, 页码: 1-9 作者: Zhan, ZH (Zhan, Zhao-Hui)[ 1 ]; You, ZH (You, Zhu-Hong)[ 2 ]; Li, LP (Li, Li-Ping)[ 2 ]; Zhou, Y (Zhou, Yong)[ 1 ]; Yi, HC (Yi, Hai-Cheng)[ 2 ] \| 收藏 \| 浏览/下载：27/0 \| 提交时间：2018/10/19 Ncrna-protein Interactions Pssm Lightgbm Pseudo-zernike Moments K-mers
	Efficient optimization approach for fast GPU computation of Zernike moments 期刊论文 OAI收割 Journal of Parallel and Distributed Computing, 2018, 卷号: 111, 页码: 104-114 作者: Xuan, Y. B.; Li, D. Y.; Han, W. \| 收藏 \| 浏览/下载：13/0 \| 提交时间：2019/09/17 Zernike moments GPU Reordering image pixels Addressing diagonal in advance recognition algorithm features face Computer Science
	3D model retrieval using constructive-learning for cross-model correlation 期刊论文 OAI收割 Neurocomputing, 2018, 卷号: 275, 页码: 2019-01-09 作者: Yang, J. B.; Zhao, J.; Sun, Q. \| 收藏 \| 浏览/下载：14/0 \| 提交时间：2019/09/17 3D model retrieval Cross-model correlation Constructive-learning 3-d object retrieval zernike moments hyper-graphs recognition search descriptor databases images views 2-d Computer Science
	Vision-Based Traffic Sign Recognition System for Intelligent Vehicles 期刊论文 OAI收割 advances in intelligent systems and computing, 2014, 卷号: 215, 页码: 347-362 作者: Yang J(杨静); Kong B(孔斌) 收藏 \| 浏览/下载：20/0 \| 提交时间：2014/12/03 Traffic sign recognition Simple vector filter Pseudo-Zernike moments Random forests
	Image registration based on Mexican-hat wavelets and pseudo-Zernike moments (EI CONFERENCE) 会议论文 OAI收割 2012 World Automation Congress, WAC 2012, June 24, 2012 - June 28, 2012, Puerto Vallarta, Mexico 作者: Liu Y.; Liu Y.; Liu Y. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 Image registration is a key technique in pattern recognition and image processing and it is widely used in many application areas such as computer vision remote sensing image fusion and object tracking. A method for image registration combining Mexican-hat wavelets and pseudo-Zernike moments is proposed. Firstly feature points are extracted using scale-interaction Mexican-hat wavelets in the reference image and sensed image respectively. Then pseudo-Zernike moments are used to match them and classical RANSAC used to eliminate the wrong matches. And then the well match points are used to estimate the best affine transform parameters by least squares minimization. At last the sensed image is transformed and resampled to accomplish the image registration. The experiments indicate that the proposed algorithm extracts feature points and matches them exactly and eliminates wrong matched points effectively and achieves nice registration results. 2012 TSI Press.
	A Robust Traffic Sign Recognition System for Intelligent Vehicles 会议论文 OAI收割 proceedings of the sixth international conference on image and graphics (icig 2011), 安徽合肥, 2011-08-12 作者: Yang J(杨静); Kong B(孔斌) 收藏 \| 浏览/下载：23/0 \| 提交时间：2014/12/03 traffic sign recognition simple vector filter Pseudo-Zernike moments support vector machines
	The coordinate acquisition of the sine welding seam based on Zernike moments edge detection 会议论文 OAI收割 IEEE International Conference on Automation and Logistics, Jinan, China, August 18-21, 2007 作者: Gao SY(高世一); Zhao MY(赵明扬); Zhang L(张雷); Wang LZ(王立柱); Zou YY(邹媛媛) 收藏 \| 浏览/下载：30/0 \| 提交时间：2012/06/06 Zernike moments sine welding seam edge detection coordinate acquisition seam tracking
	A novel starting-point-independent wavelet coefficient shape matching (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Hu S.; Zhu M.; Wu C.; Song H.-J. 收藏 \| 浏览/下载：18/0 \| 提交时间：2013/03/25 In many computer vision tasks in order to improve the accuracy and robustness to the noise wavelet analysis is preferred for the natural multi-resolution property. However the wavelet representation suffers from the dependency of the starting point of the sampled contour. For overcoming the problem that the wavelet representation depends on the starting point of the sampled contour the Zernike moments are introduced and a novel Starting-Point-lndependent wavelet coefficient shape matching algorithm is presented. The proposed matching algorithm firstly gains the object contours and give the translation and scale invariant object shape representation. The object shape representation is converted to the dyadic wavelet representation by the wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments consider the Zernike moments as the feature vector to calculate the dissimilarity between the object and template image which overcoming the problem of dependency of starting point. The experimental results have proved the proposed algorithm to be efficient precise and robust.