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Titlebook: Image and Signal Processing; 3rd International Co Abderrahim Elmoataz,Olivier Lezoray,Driss Mammass Conference proceedings 2008 Springer-Ve

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發(fā)表于 2025-3-21 17:55:32 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Image and Signal Processing
副標(biāo)題3rd International Co
編輯Abderrahim Elmoataz,Olivier Lezoray,Driss Mammass
視頻videohttp://file.papertrans.cn/462/461498/461498.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Image and Signal Processing; 3rd International Co Abderrahim Elmoataz,Olivier Lezoray,Driss Mammass Conference proceedings 2008 Springer-Ve
描述This book constitutes the refereed proceedings of the Third International Conference on Image and Signal Processing, ICISP 2008, held in Cherbourg-Octeville, France, in July 2008. The 48 revised full papers and 22 revised poster papers presented were carefully reviewed and selected from 193 submissions. The papers are organized in topical sections on image filtering, image segmentation, computer vision, feature extraction, pattern recognition, graph-based representations, motion detection and estimation, new interfaces, document processing, and signal processing.
出版日期Conference proceedings 2008
關(guān)鍵詞adaptive systems; algorithmic learning; ant colony optimization; biometrics; character recognition; class
版次1
doihttps://doi.org/10.1007/978-3-540-69905-7
isbn_softcover978-3-540-69904-0
isbn_ebook978-3-540-69905-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag GmbH Germany, part of Springer Nature 2008
The information of publication is updating

書目名稱Image and Signal Processing影響因子(影響力)




書目名稱Image and Signal Processing影響因子(影響力)學(xué)科排名




書目名稱Image and Signal Processing網(wǎng)絡(luò)公開度




書目名稱Image and Signal Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Image and Signal Processing被引頻次




書目名稱Image and Signal Processing被引頻次學(xué)科排名




書目名稱Image and Signal Processing年度引用




書目名稱Image and Signal Processing年度引用學(xué)科排名




書目名稱Image and Signal Processing讀者反饋




書目名稱Image and Signal Processing讀者反饋學(xué)科排名




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Uniqueness Filtering for Local Feature Descriptors in Urban Building Recognitionan be used for selection purposes. To evaluate our approach, we carried out experiments in urban building recognition domains with different datasets. The results show a significant improvement not only in recognition speed, as a result of using fewer features, but also in the performance of the system with selected features.
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Dynamic Human Fatigue Detection Using Feature-Level Fusionorithm is applied to extract the most discriminative features and construct a strong classifier for fatigue detection. The test data contains 600 image sequences from thirty people. Experimental results show the validity of the proposed approach, and the correct rate is much better than the baselines.
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Improved Phase Correlation Matchingxtends the images with new pixels having decaying values. The technique is compared with two recent methods on cluttered, noisy, blurred, and slightly rotated scenes. The results show that the proposed method outperforms both of them, especially when the object is away from the central region in the image.
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Real Time Monocular Depth from Defocusnce to the depth by tacking account of the parameters of the optical system. We present a set of results on real images showing the performance of the method and its limits. The computing times which we measured make possible the use of our algorithm at video rate.
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Conference proceedings 2008eville, France, in July 2008. The 48 revised full papers and 22 revised poster papers presented were carefully reviewed and selected from 193 submissions. The papers are organized in topical sections on image filtering, image segmentation, computer vision, feature extraction, pattern recognition, gr
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RETRACTED CHAPTER: Reinstating Floyd-Steinberg: Improved Metrics for Quality Assessment of Error Difch. Using empirical observation, we give a method for creating computationally efficient, image-independent, model-based metrics for this quality assessment. Finally, we use the properties of error diffusion displacement to justify Floyd and Steinberg’s well-known choice of algorithm coefficients.
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