或者发神韵
发表于 2025-3-28 17:21:14
,Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study,ning methods for medical image classification. The benchmark consists of two chest X-ray datasets for 19- and 20-way thorax disease classification, containing classes with as many as 53,000 and as few as 7 labeled training images. We evaluate both standard and state-of-the-art long-tailed learning m
Jocose
发表于 2025-3-28 21:17:02
http://reply.papertrans.cn/27/2628/262735/262735_42.png
误传
发表于 2025-3-28 23:43:17
http://reply.papertrans.cn/27/2628/262735/262735_43.png
intricacy
发表于 2025-3-29 07:05:30
,Noisy Label Classification Using Label Noise Selection with Test-Time Augmentation Cross-Entropy anlabel noise selection process. Moreover, the proposed NoiseMix not only outperformed the state-of-the-art methods in the classification performance but also showed the most robustness to the label noise in the classifier learning.
我悲伤
发表于 2025-3-29 07:14:59
,CSGAN: Synthesis-Aided Brain MRI Segmentation on 6-Month Infants,E) module in the generators of CycleGAN, by embedding semantic information into networks to keep the brain anatomical structure consistent across 6-month and 12-month brain MRI. After that, we train an initial segmentation model on these augmented data to overcome the isointense problem in 6-months
habile
发表于 2025-3-29 14:50:31
,A Stratified Cascaded Approach for Brain Tumor Segmentation with the Aid of Multi-modal Synthetic Docalization module, focusing the training and inference in the vicinity of the tumor. Finally, to identify which tumor grade segmentation model to utilize at inference time, we train a dense, attention-based 3D classification model. The obtained results suggest that both stratification and the addit
草本植物
发表于 2025-3-29 18:18:01
http://reply.papertrans.cn/27/2628/262735/262735_47.png
热烈的欢迎
发表于 2025-3-29 20:38:10
Climate Change Signals and Responseevaluate data quality based on the marginal change of the largest singular value after excluding the data point in the dataset. We conduct extensive experiments on a pathology dataset. Our results indicate the effectiveness and efficiency of our proposed methods for selecting the most valuable data to label.
animated
发表于 2025-3-30 01:42:06
http://reply.papertrans.cn/27/2628/262735/262735_49.png
Stagger
发表于 2025-3-30 05:59:57
,Disentangling a Single MR Modality,ic resonance images. Moreover, we propose a new information-based metric to quantitatively evaluate disentanglement. Comparisons over existing disentangling methods demonstrate that the proposed method achieves superior performance in disentanglement and cross-domain image-to-image translation tasks.