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Titlebook: Computer Analysis of Images and Patterns; CAIP 2019 Internatio Mario Vento,Gennaro Percannella,Manzoor Razaak Conference proceedings 2019 S

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书目名称Computer Analysis of Images and Patterns
副标题CAIP 2019 Internatio
编辑Mario Vento,Gennaro Percannella,Manzoor Razaak
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Computer Analysis of Images and Patterns; CAIP 2019 Internatio Mario Vento,Gennaro Percannella,Manzoor Razaak Conference proceedings 2019 S
描述.This book constitutes the refereed proceedings of two workshops held at the 18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019: First Workshop on Deep-learning based Computer Vision for UAV, DL-UAV 2019, and the First Workshop on Visual Computing and Machine Learning for Biomedical Applications, ViMaBi 2019.. The 12 papers presented in this volume were carefully reviewed and selected from 16 submissions and focus on all aspects of visual computing and machine learning for biomedical applications, and deep-learning based computer vision for UAV..
出版日期Conference proceedings 2019
关键词artificial intelligence; Human-Computer Interaction (HCI); image processing; machine learning; machine l
版次1
doihttps://doi.org/10.1007/978-3-030-29930-9
isbn_softcover978-3-030-29929-3
isbn_ebook978-3-030-29930-9Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Liat Margolis,Alexander Robinson method for estimating the crop and weed distribution from images captured by a UAV. The proposed approach runs on an embedded board equipped with a GPU. Quantitative experimental results have been obtained using real images from two different public datasets. The results demonstrate the effectiveness of the proposed approach.
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https://doi.org/10.1007/3-540-37671-2c retinopathy. This segmentation is necessary to evaluate the state of the vascular network and to detect abnormalities (aneurysms, hemorrhages, etc). Many image processing and machine learning methods have been developed in recent years in order to achieve this segmentation. These methods are diffi
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,Modèles micro-macro pour les fluides,uld perform. Breast density is one of the most important breast cancer risk factor and it represents the amount of fibroglandular tissue with respect to fat tissue as seen on a mammographic exam. However, it is not easy to include it in risk models because of its variability among women and its qual
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https://doi.org/10.1007/3-540-37671-2GSP) for the analysis of neuroimaging data. Thus, a GSP-based approach is proposed and validated for the classification of autism spectrum disorder (ASD). More specifically, the resting state functional magnetic resonance imaging (rs-fMRI) time series of each brain subject are characterized by sever
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