Results 261 to 270 of about 9,428,499 (297)

A new texture representation with multi-scale wavelet feature

SPIE Proceedings, 2006
The existing methods for texture modeling include co-occurrence statistics, filter banks and random fields. However most of these methods lack of capability to characterize the different scale of texture effectively. In this paper, we propose a texture representation which combines local scale feature, amplitude and phase of wavelet modules in multi ...
Sheng Yi, Hanqiang Cao, Xutao Li, Miao Liu   +3 more
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A Novel Multi-scale Representation for 2-D Shapes

2007
We present an original approach for 2-D shapes description. Based on a multi-scale analysis of closed contours, this method deals with the differential turning angle. The input contour is progressively low-pass filtered by decreasing the filter bandwidth. The output contour thus becomes increasingly smooth. At each iteration of the filtering we extract
Kidiyo Kpalma, Joseph Ronsin
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Multi-scale structural kernel representation for object detection

Pattern Recognition, 2021
Abstract Existing high-performance object detection methods greatly benefit from the powerful representation ability of deep convolutional neural networks (CNNs). Recent researches show that integration of high-order statistics remarkably improves the representation ability of deep CNNs.
Hao Wang 0073, Qilong Wang 0001, Peihua Li, Wangmeng Zuo   +3 more
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Assessment on uncertainty of multi-scale representation of point cluster

2010 18th International Conference on Geoinformatics, 2010
In this paper, it firstly establishes the assessment contents on uncertainty of multi-scale representation of point cluster around the process of multi-scale representation of point cluster and its spatial analysis, which includes positional uncertainty and uncertainty of spatial analysis conclusions; the assessment index K and the quantitative model ...
Feng Xu, Jianhua He, Shengnan Zhang
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Multi-scale counting and difference representation for texture classification

The Visual Computer, 2017
Multi-scale analysis has been widely used for constructing texture descriptors by modeling the coefficients in transformed domains. However, the resulting descriptors are not robust to the rotated textures when performing texture classification. To alleviate this problem, we in this paper propose a multi-scale counting and difference representation ...
Yongsheng Dong, Jinwang Feng, Chunlei Yang, Xiaohong Wang, Lintao Zheng, Jiexin Pu   +5 more
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Smooth surfaces for multi-scale shape representation

1995
The skin of a set of weighted points in ld is defined as a differentiable and orientable (d}- 1)-manifold surrounding the points. The skin varies continuously with the points and weights and at all times maintains the homotopy equivalence between the dual shape of the points and the body enclosed by the skin.
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Rethinking Multi-Scale Representations in Deep Deraining Transformer

Proceedings of the AAAI Conference on Artificial Intelligence
Existing Transformer-based image deraining methods depend mostly on fixed single-input single-output U-Net architecture. In fact, this not only neglects the potentially explicit information from multiple image scales, but also lacks the capability of exploring the complementary implicit information across different scales.
Hongming Chen 0004, Xiang Chen 0015, Jiyang Lu, Yufeng Li 0001   +3 more
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Multi-scale Sparse Representation for Robust Face Recognition

2011 Third International Conference on Knowledge and Systems Engineering, 2011
Recently the Sparse Representation-based Classification (SRC) has been successfully used in face recognition. In SRC, a test image is coded by a linear combination of the training dictionary. In this paper, we propose a model extends from SRC named Multi-scale SRC (MSRC). The MSRC build the multi-scale dictionary for the training.
Mao X. Nguyen, Quang M. Le, Vu Pham, Trung Ngoc Tran, Bac Hoai Le   +4 more
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Learning multi-scale sparse representation for visual tracking

2014 IEEE International Conference on Image Processing (ICIP), 2014
We present a novel algorithm for learning multi-scale sparse representation for visual tracking. In our method, sparse codes with max pooling are used to form a multi-scale representation that integrates spatial configuration over patches of different sizes.
Zhengjian Kang, Edward K. Wong
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Multi-scale Deep Representation Learning for Face Detection

2018 IEEE Visual Communications and Image Processing (VCIP), 2018
In this paper, we propose a face detection method with multi-scale deep representation learning. While existing face detection methods have achieved good performance, they fail to consider the large intra-class variations between faces in the prediction stage and the relation between multi-scale proposals in the proposal stage.
Jifei Han, Jiwen Lu, Jianjiang Feng, Jie Zhou 0001   +3 more
openaire   +2 more sources