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Titlebook: Computer Analysis of Images and Patterns; 19th International C Nicolas Tsapatsoulis,Andreas Panayides,Mario Vento Conference proceedings 20

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發(fā)表于 2025-3-21 17:58:09 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computer Analysis of Images and Patterns
副標(biāo)題19th International C
編輯Nicolas Tsapatsoulis,Andreas Panayides,Mario Vento
視頻videohttp://file.papertrans.cn/234/233449/233449.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer Analysis of Images and Patterns; 19th International C Nicolas Tsapatsoulis,Andreas Panayides,Mario Vento Conference proceedings 20
描述.The two volume set LNCS 13052 and 13053 constitutes the refereed proceedings of the 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021, held virtually, in September 2021...?..The 87 papers presented were carefully reviewed and selected from 129 submissions. The papers are organized in the following topical sections across the 2 volumes: 3D vision, biomedical image and pattern analysis; machine learning; feature extractions; object recognition; face and gesture, guess the age contest, biometrics, cryptography and security; and segmentation and image restoration..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; computer systems; computer vision; face recognition; image analysis; image codin
版次1
doihttps://doi.org/10.1007/978-3-030-89131-2
isbn_softcover978-3-030-89130-5
isbn_ebook978-3-030-89131-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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Measurement and Measurement Uncertainty,earn hash codes for fine-grained image similarity search in natural images and a two-stage method for efficiently searching binary hash codes using Elasticsearch (ES). In the first stage, a coarse search based on short hash codes is performed using multi-index hashing and ES terms lookup of neighbor
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Systems Analysis for Water Technology The architecture of the Siamese network is a combination of two multi-filter multi-scale deep convolutional neural networks (MFMS DCNN). Initially, the Siamese network is trained by utilizing the image-level semantic labels of the image pairs in the dataset. The features of the image pairs are obta
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System Boundaries and Material Balances, medical counterparts, but the task entrusted to the scanner operator is different from that of the doctor. The scanner operator’s task is to find if there are any dangerous objects in the X-ray image. The operator has to evaluate the shape and kind of material of the scanned objects within a few se
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Hydraulic Residence Time Distribution,nalysis of biomedical image with blood vessels highlighting, graph-shape structures, cracks detection, satellite images or remote sensing data. Multi-scale processing of line feature is essentially required for the extraction of more relevant information or line structures of heterogeneous widths. I
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System Boundaries and Material Balances,e correct articulation of such Descriptor Manifold (DM) by the camera poses is the cornerstone for precise Appearance-based Localization (AbL), which implies knowing the correspondent descriptor for any given pose of the camera in the environment. Since such correspondences are only given at sample
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