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检索条件"机构=Image Proc. Pattern Recognition Inst"
42 条 记 录,以下是1-10 订阅
排序:
Mushroom Classification Based on Deep Residual Network  4
Mushroom Classification Based on Deep Residual Network
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4th IEEE International Conference on pattern recognition and Machine Learning, PRML 2023
作者: Feng, Ju Ling, Xufeng Wang, Yubo Yang, Jie Shanghai Normal University Tianhua College School of Artificial Intelligence Shanghai China Shanghai Acoustics Laboratory Chinese Academy of Sciences Shanghai China Inst. of Image Proc. and Pattern Recog. and Inst. of Medical Robotics Shanghai Jiaotong University Shanghai China
Due to the similarity in mushroom features and the difficulty in distinguishing between poisonous and nonpoisonous varieties, mushrooms pose a threat to human health. To address the challenge of mushroom classificatio... 详细信息
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Characterizing Obstacle-Avoiding Paths Using Cohomology Theory
Characterizing Obstacle-Avoiding Paths Using Cohomology Theo...
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14th International Conference on Computer Analysis of images and patterns (CAIP)
作者: Dlotko, Pawel Kropatsch, Walter G. Wagner, Hubert Jagiellonian Univ Inst Comp Sci PL-31007 Krakow Poland Vienna Univ Technol Pattern Recognition & Image Proc Grp Vienna Austria
In this paper, we investigate the problem of analyzing the shape of obstacle-avoiding paths in a space. Given a d-dimensional space with holes, representing obstacles, we ask if certain paths are equivalent, informall... 详细信息
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Object localization based on Markov random fields and symmetry interest points
Object localization based on Markov random fields and symmet...
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10th International Conference on Medical image Computing and Computer-Assisted Intervention (MICCAI 2007)
作者: Donner, Rene Micusik, Branislav Langs, Georg Szumilas, Lech Peloschek, Philipp Friedrich, Klaus Bischof, Horst Graz Univ Technol Inst Comp Graph & Vis A-8010 Graz Austria Vienna Univ Technol Pattern Recognition & Image Proc Grp Vienna Austria Ecole Cent Paris GALEN Grp Math Appl Syst Paris France Med Univ Vienna Dept Radiol Vienna Austria
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov Random Fields, and the detection is ... 详细信息
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Line-based scan compression algorithm suitable for remote sensing images
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Yuhang Xuebao/Journal of Astronautics 2005年 第1期26卷 60-65+76页
作者: Wang, Zhen-Hua Tian, Jin-Wen Liu, Jian Lab. for Image Proc. Inst. for Pattern Recognition Huazhong Univ. of Sci. and Technol. Wuhan 430074 China
In this paper, a line-based scan image compression algorithm with low complexity was presented. The algorithm was based on Christos Chrysalis's line-based wavelet transformation coding. There was not image tiling ... 详细信息
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Regularized restoration algorithm of astronautical turbulence-degraded images using maximum-likelihood estimation
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Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves 2005年 第2期24卷 130-134页
作者: Hong, Han-Yu Zhang, Tian-Xu Yu, Guo-Liang Lab. of Image Proc. Inst. for Pattern Recognition and AI Huazhong Univ. of Sci. and Technol. Wuhan 430074 China
A regularized restoration algorithm based on maximum-likelihood estimation was presented for restoring object images from the noisy turbulence-degraded images. The logarithmic maximum-likelihood function for multi-fra... 详细信息
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Vision pyramids that do not grow too high
Vision pyramids that do not grow too high
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作者: Kropatsch, Walter G. Haxhimusa, Yll Pizlo, Zygmunt Langs, Georg Inst. of Computer Aided Automation Pattern Recog. Image Proc. G. Vienna University of Technology Favoritenstrasse 9 A-1040 Vienna Austria Department of Psychological Sciences Sch. of Elec. and Comp. Engineering Purdue University West Lafayette IN 47907-1364 United States Inst. for Comp. Graphics and Vision Graz University of Technology Inffeldgasse 16 2.OG A-8010 Graz Austria
In irregular pyramids, their vertical structure is not determined beforehand as in regular pyramids. We present three methods, all based on maximal independent sets from graph theory, with the aim to simulate the majo... 详细信息
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Multisensor aerial image registration using direct histogram specification
Multisensor aerial image registration using direct histogram...
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Conference proc.eding - 2004 IEEE International Conference on Networking, Sensing and Control
作者: Tuo, Hongya Zhang, Lin Liu, Yuncai Inst. of Image Proc./Pattern Recog. Shanghai Jiao Tong University Shanghai
Multisensor image registration is a difficult problem. In this paper, we give a new registration method using direct histogram specification technique. We find that after using histogram specification, the resulting i... 详细信息
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The role of context and model in urban aerial image interpretation focusing on buildings
The role of context and model in urban aerial image interpre...
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Conference proc.eding - 2004 IEEE International Conference on Networking, Sensing and Control
作者: Peng, Jing Liu, Yuncai Inst. of Image Proc./Pattern Recog. Shanghai Jiaotong University Shanghai China
Guided by a building concept model, which interprets building into different levels and scales, this paper presents a method to extract buildings in monocular urban aerial images without priori illuminating or orienta... 详细信息
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Estimation of camera pose using 20-30 occluded corner correspondence
Estimation of camera pose using 20-30 occluded corner corres...
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2004 7th International Conference on Signal proc.ssing proc.edings (ICSP'04)
作者: Fanhuai, Shi Xiaoyun, Zhang Hongjian, Liu Yuncai, Liu Inst. Image Proc. and Pattern Recog. Shanghai Jiaotong University Shanghai 200030 China
In this paper, we investigate how camera pose can be estimated from 2D to 3D corner correspondence when vertex of the corner is occluded. We show that the image coordinate of the occluded vertex can be easily estimate... 详细信息
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Nonlinear spectral similarity measure
Nonlinear spectral similarity measure
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2004 IEEE International Geoscience and Remote Sensing Symposium proc.edings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004
作者: Hong, Tang Tao, Fang Pengfei, Shi Inst. Image Proc. and Pattern Recog. Shanghai Jiao Tong University Shanghai 200030 China
A novel method for spectral similarity measure, which is called nonlinear spectral similarity measure, is presented in this paper. In this method, all original spectral vectors are, firstly, nonlinearly transformed in... 详细信息
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