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Titlebook: Image Analysis and Processing — ICIAP 2015; 18th International C Vittorio Murino,Enrico Puppo Conference proceedings 2015 Springer Nature S

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书目名称Image Analysis and Processing — ICIAP 2015
副标题18th International C
编辑Vittorio Murino,Enrico Puppo
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Image Analysis and Processing — ICIAP 2015; 18th International C Vittorio Murino,Enrico Puppo Conference proceedings 2015 Springer Nature S
描述The two-volume set LNCS 9279 and 9280 constitutes the refereed proceedings of the 18th International Conference on Image Analysis and Processing, ICIAP 2015, held in Genoa, Italy, in September 2015. The 129 papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in the following seven topical sections: video analysis and understanding, multiview geometry and 3D computer vision, pattern recognition and machine learning, image analysis, detection and recognition, shape analysis and modeling, multimedia, and biomedical applications.
出版日期Conference proceedings 2015
关键词computer vision; image processing; multimodal retrieval; pattern recognition; video processing; 3D comput
版次1
doihttps://doi.org/10.1007/978-3-319-23234-8
isbn_softcover978-3-319-23233-1
isbn_ebook978-3-319-23234-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2015
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A Gravitational Model for Plant Classification Using Adaxial Epidermis Texturemis. To accomplish this task, we propose combining complexity analysis methods with a gravitational collapsing system to extract texture features from adaxial epidermis samples. Experimental results show that this combination of techniques surpasses traditional and state-of-the-art methods in both grayscale and color images of adaxial epidermis.
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Bounded Non-Local Means for Fast and Effective Image Denoisingg function. Unlike previous approaches, our technique mathematically guarantees all highly correlated patches to be accounted for while discarding dissimilar ones, this providing not only faster speed but improved denoising too.
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Hierarchical Image Representation Using Deep Networkpatial information into BoW representation by learning different networks and visual words for each quadrant regions. We compare the proposed algorithm with the similar approaches in the literature using a challenging 10-class-dataset, CIFAR-10.
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On Spatiochromatic Features in Natural Images Statistics tested on a large database of RAW images. Our experiments also show that the spatiochromatic covariance decays exponentially with the spatial distance between pairs of pixels and not as a power law as it is commonly assumed.
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