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Titlebook: Image Analysis and Processing - ICIAP 2023 Workshops; Udine, Italy, Septem Gian Luca Foresti,Andrea Fusiello,Edwin Hancock Conference proce

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書目名稱Image Analysis and Processing - ICIAP 2023 Workshops
副標(biāo)題Udine, Italy, Septem
編輯Gian Luca Foresti,Andrea Fusiello,Edwin Hancock
視頻videohttp://file.papertrans.cn/462/461361/461361.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Image Analysis and Processing - ICIAP 2023 Workshops; Udine, Italy, Septem Gian Luca Foresti,Andrea Fusiello,Edwin Hancock Conference proce
描述The two-volume set LNCS 14365 and 14366 constitutes the papers of workshops hosted by the 22nd International Conference on Image Analysis and Processing, ICIAP 2023, held in Udine, Italy, in September 2023..In total, 72 workshop papers and 10 industrial poster session papers have been accepted for publication.?.Part II of the set, volume 14366, contains 41 papers from the following workshops:.– Medical Imaging Hub:.? Artificial Intelligence and Radiomics in Computer-Aided Diagnosis (AIR-.CAD).? Multi-Modal Medical Imaging Processing (M3IP).? Federated Learning in Medical Imaging and Vision (FedMed).– Digital Humanities Hub:.? Artificial Intelligence for Digital Humanities (AI4DH).? Fine Art Pattern Extraction and Recognition (FAPER).? Pattern Recognition for Cultural Heritage (PatReCH).? Visual Processing of Digital Manuscripts: Workflows, Pipelines, Best.Practices (ViDiScript).
出版日期Conference proceedings 2024
關(guān)鍵詞Pattern Recognition; Pattern Recognition; Machine Learning and Deep Learning; 3D Computer Vision and Ge
版次1
doihttps://doi.org/10.1007/978-3-031-51026-7
isbn_softcover978-3-031-51025-0
isbn_ebook978-3-031-51026-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Image Analysis and Processing - ICIAP 2023 Workshops978-3-031-51026-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/461361.jpg
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https://doi.org/10.1007/978-3-031-51026-7Pattern Recognition; Pattern Recognition; Machine Learning and Deep Learning; 3D Computer Vision and Ge
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Vision Transformers for?Breast Cancer Histology Image Classification stack of transformer layers, with each layer consisting of a multi-head self-attention mechanism and a position-wise feed-forward network, and it is trained with different strategies and configurations, including pretraining, resize dimension, data augmentation, patch overlap, and patch size, to in
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Assessing the Robustness and Reproducibility of CT Radiomics Features in Non-small-cell Lung Carcinoon-small-cell lung carcinoma (NSCLC). Specifically, the impact of manual segmentation on radiomics feature values and their variability were assessed. Therefore, 63 patients affected by squamous cell carcinoma (SCC) and adenocarcinoma (ADC) were retrospectively collected from a public dataset. Origi
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