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	Semisupervised Progressive Representation Learning for Deep Multiview Clustering 期刊论文 OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 15 作者: Chen, Rui; Tang, Yongqiang; Xie, Yuan; Feng, Wenlong; Zhang, Wensheng \| 收藏 \| 浏览/下载：19/0 \| 提交时间：2023/11/17 Representation learning Training Data models Task analysis Complexity theory Semisupervised learning Optimization Deep clustering multiview clustering progressive sample learning semisupervised learning
	A local feature based simplification method for animated mesh sequence (EI CONFERENCE) 会议论文 OAI收割 2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010, April 16, 2010 - April 18, 2010, Chengdu, China 作者: Wang B.; Wang B.; Zhao J.; Zhang S. 收藏 \| 浏览/下载：23/0 \| 提交时间：2013/03/25 Although animated meshes are frequently used in numerous domains only few works have been proposed until now for simplifying such data. In this paper we propose a new method for generating progressive animated models based on local feature analysis and deformation area preservation. We propose the use of solid angle and height value for a non-hyperbolic vertex to define the local feature parameter. This local factor is embedded to the vertex quadric error matrix when calculating the edge collapse cost. In order to preserve the areas with large deformation we add deformation degree weight to the aggregated quadric errors when computing the unified edge contraction sequence. Finally a mesh optimization process is proposed to further reduce the geometric distortion for each frame. Our approach is fast easy to implement and as a result good quality dynamic approximations with well-preserved fine details can be generated at any given frame. 2010 IEEE.
	efficient monitoring of skyline queries over distributed data streams 期刊论文 OAI收割 KNOWLEDGE AND INFORMATION SYSTEMS, 2010, 卷号: 25, 期号: 3, 页码: 575-606 Sun Shengli; Huang Zhenghua; Zhong Hao; Dai Dongbo; Liu Hongbin; Li Jinjiu \| 收藏 \| 浏览/下载：29/0 \| 提交时间：2011/05/23 Distributed data streams Skyline Communication-optimal processing Progressive refinement
	An improved method for generating multiresolution animation models (EI CONFERENCE) 会议论文 OAI收割 2009 11th IEEE International Conference on Computer-Aided Design and Computer Graphics, CAD/Graphics 2009, August 19, 2009 - August 21, 2009, Huangshan, China 作者: Zhang S. 收藏 \| 浏览/下载：36/0 \| 提交时间：2013/03/25 In computer graphics animated models are widely used to represent time-varying data. In this paper we propose an improved method to generate multiresolution animation models. We use a curvature sensitive quadric error metric (QEM) criterion as our basic measurement which can preserve local features on the surface. We append a deformation weight to the aggregated edge contraction cost for the whole animation to preserve areas with large deformation. At last we introduce a mesh optimization method to deal with the animation sequence which can efficiently improve the temporal coherence and reduce visual artifacts. The results show our approach is efficient easy to implement and good quality progressive animation models can be generated at any level of detail. 2009 IEEE.
	Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：41/0 \| 提交时间：2013/03/25 An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image thus facilitating accurate diagnosis of course at the expense of higher bit rates i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization wavelet coding neural networks and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1 or even more) they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image but the achievable compression ratios are only of the order 2:1 up to 4:1. In our paper we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance so that all the low rate codes are included at the beginning of the bit stream. Typically the encoding process stops when the target bit rate is met. Similarly the decoder can interrupt the decoding process at any point in the bil stream and still reconstruct the image. Therefore a compression scheme generating an embedded code can start sending over the network the coarser version of the image first and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.
	An. approach for integrating 3D GIS, virtual reality and the Internet 会议论文 OAI收割 IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, New York Yu, WY; Yang, CJ; Chen, FX; Yang, JY; Le, XQ 收藏 \| 浏览/下载：22/0 \| 提交时间：2014/12/07 3D-GIS virtual reality data model spatial analysis progressive data transfer