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Titlebook: Advanced Concepts for Intelligent Vision Systems; 17th International C Jacques Blanc-Talon,Cosimo Distante,Paul Scheunder Conference procee

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樓主: Adentitious
61#
發(fā)表于 2025-4-1 05:01:20 | 只看該作者
https://doi.org/10.1007/978-3-663-20393-3 algorithm aims in the first time to detect user’s face and their eyes in the second time. The eyes gesture recognition is based on fuzzy inference system. We deployed this algorithm on an android-based tablet and we asked 8 volunteers to test it. The obtained results proved that this system has promising and competitive results.
62#
發(fā)表于 2025-4-1 07:08:12 | 只看該作者
Berechnungstheorie für Informatikeruences captured in adverse weather conditions and in an urban scenario at night-time. Experimental results demonstrate the effectiveness of the proposed approach in terms of both classification accuracy and computational speed.
63#
發(fā)表于 2025-4-1 11:06:15 | 只看該作者
0302-9743 r Intelligent Vision Systems, ACIVS 2016, held in Lecce, Italy, in October 2016..The 64 revised full papers presented in this volume were carefully selected from 137 submissions. They deal with?classical low-level image processing techniques; image and video compression;?3D; security and forensics;
64#
發(fā)表于 2025-4-1 17:55:47 | 只看該作者
Vergleich zwischen Messung und Rechnung,ons. We carried out several tests using radial basis neural network (RBF) for classification, a comparative study against stat-of-the-art methods shows that our technique is faster, simple and gives higher accuracy performance comparing to discrete transform based techniques and other methods proposed in literature.
65#
發(fā)表于 2025-4-1 21:23:40 | 只看該作者
https://doi.org/10.1007/978-3-642-91601-4ical information. So accurate segmentation is difficult. The proposed method adds joint constraints of shape, parallelism and intensity in a level-set framework to simultaneously extract myocardium from rest and stress images. Results are compared to classical level-set segmentation.
66#
發(fā)表于 2025-4-1 23:42:26 | 只看該作者
https://doi.org/10.1007/978-3-322-84915-1atically gives a probability of alteration for any area of the image, using a local analysis of noise density. We consider both Gaussian and Poisson noise components to modelize the noise in the image. The efficiency and robustness of our method is demonstrated on a large set of images generated with an automated splicing.
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