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Titlebook: Computer Vision – ECCV 2022 Workshops; Tel Aviv, Israel, Oc Leonid Karlinsky,Tomer Michaeli,Ko Nishino Conference proceedings 2023 The Edit

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11#
發(fā)表于 2025-3-23 11:01:51 | 只看該作者
ReLaX: Retinal Layer Attribution for?Guided Explanations of?Automated Optical Coherence Tomography Cans requires trained eye care professionals who are still prone to making errors. With better systems for diagnosis, many cases of vision loss caused by retinal disease could be entirely avoided. In this work, we present ReLaX, a novel deep learning framework for explainable, accurate classification
12#
發(fā)表于 2025-3-23 15:27:30 | 只看該作者
Neural Registration and?Segmentation of?White Matter Tracts in?Multi-modal Brain MRI tractography workflows rely on classical registration tools that prospectively align the multiple brain MRI modalities required for the task. Brain lesions and patient motion may challenge the robustness and accuracy of these tool, eventually requiring additional manual intervention. We present a n
13#
發(fā)表于 2025-3-23 21:17:38 | 只看該作者
Complementary Phase Encoding for?Pair-Wise Neural Deblurring of?Accelerated Brain MRIver, due to long scanning times and capital costs, access to MRI lags behind CT. Typical brain protocols lasting over 30?min set a clear limitation to patient experience, scanner throughput, operation profitability, and lead to long waiting times for an appointment..As image quality, in terms of spa
14#
發(fā)表于 2025-3-23 22:37:17 | 只看該作者
15#
發(fā)表于 2025-3-24 04:27:32 | 只看該作者
16#
發(fā)表于 2025-3-24 07:20:18 | 只看該作者
Simultaneous Detection and?Classification of?Partially and?Weakly Supervised Cellsng and grading at the slide level is routinely performed by pathologists, but analysis at the cell level, often desired in personalized cancer treatment, is both impractical and non-comprehensive. With its remarkable success in natural images, deep learning is already the gold standard in computatio
17#
發(fā)表于 2025-3-24 14:15:51 | 只看該作者
18#
發(fā)表于 2025-3-24 14:50:41 | 只看該作者
Unacceptable Weapons: Gas and Bacteria,ods and benchmark establish the state-of-the-art for this low-level vision inverse problem, and generating realistic raw sensor readings can potentially benefit other tasks such as denoising and super-resolution.
19#
發(fā)表于 2025-3-24 21:04:00 | 只看該作者
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發(fā)表于 2025-3-24 23:13:32 | 只看該作者
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