hauteur
发表于 2025-3-27 00:54:50
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentationalize as well to new patient cohorts, impeding their widespread adoption into real clinical contexts. One strategy to create a more diverse, generalizable training set is to naively pool datasets from different cohorts. Surprisingly, training on this . does not necessarily increase, and may even red
Kidnap
发表于 2025-3-27 03:05:19
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巨头
发表于 2025-3-27 06:04:41
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Atrium
发表于 2025-3-27 09:40:45
Unsupervised Domain Adaption via Similarity-Based Prototypes for Cross-Modality Segmentationn applied to unseen data. Since the model is sensitive to domain shift, unsupervised domain adaption attempts to reduce the domain gap and avoid costly annotation of unseen domains. This paper proposes a novel framework for cross-modality segmentation via similarity-based prototypes. In specific, we
传授知识
发表于 2025-3-27 13:35:56
Classification and Generation of Microscopy Images with Plasmodium Falciparum via Artificial Neural specific datasets. Indeed, even if over-fitting is avoided during the improvements of computer vision applications, large differences are expected. Differences might be related to settings of camera (exposure, white balance settings, etc.) and different blood film slides preparation. Generative adve
Encapsulate
发表于 2025-3-27 17:56:45
Contrast and Resolution Improvement of POCUS Using Self-consistent CycleGAN physical examination. Recently, many methods were proposed to reduce the size and power consumption of the system while improving the visual quality, but hand-held POCUS devices still have inferior image contrast and spatial resolution compared to the high-end ultrasound systems. To address this, h
forecast
发表于 2025-3-27 23:21:09
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expire
发表于 2025-3-28 03:32:33
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协迫
发表于 2025-3-28 06:44:03
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detach
发表于 2025-3-28 11:20:49
Conference proceedings 2021onsistent across different domains. ..For FAIR 2021, 10 papers from 17 submissions were accepted for publication. They focus on Image-to-Image Translation particularly for low-dose or low-resolution settings; Model Compactness and Compression; Domain Adaptation and Transfer Learning; Active, Continual and Meta-Learning... .. .