确保 发表于 2025-3-27 00:23:29
http://reply.papertrans.cn/33/3207/320623/320623_31.png合适 发表于 2025-3-27 03:41:10
Micromachined Resonators and Circuits,hat with equal annotation effort aggregated uncertainties across image augmentations yield improved results compared to a baseline without augmentations, however certain configurations can be detrimental for the performance of the resulting model.Vldl379 发表于 2025-3-27 05:46:45
Review of Microinjection Systems,ills. This research contributes to our understanding of how practical LLMs are in real-world information extraction tasks and highlights the differences in performance among various state-of-the-art models.CHAFE 发表于 2025-3-27 12:33:57
https://doi.org/10.1007/978-1-4471-4597-4aller than that found in the selected traditional architectures for this study. It shows the potential of the Q-NAS algorithm and highlights the importance of efficient model design in the context of accurate and feature-aware medical image analysis.MIR 发表于 2025-3-27 17:11:03
James D. Lee,Jiaoyan Li,Zhen Zhang,Leyu Wangsion Trees emerged as the most effective, each achieving an accuracy of 82%. This study not only underscores the potential of machine learning in medical diagnostics but also paves the way for more accessible and efficient screening methods for neurodevelopmental disorders.Dawdle 发表于 2025-3-27 18:27:05
Active Learning with Aggregated Uncertainties from Image Augmentationshat with equal annotation effort aggregated uncertainties across image augmentations yield improved results compared to a baseline without augmentations, however certain configurations can be detrimental for the performance of the resulting model.拍下盗公款 发表于 2025-3-27 23:45:07
http://reply.papertrans.cn/33/3207/320623/320623_37.png基因组 发表于 2025-3-28 05:23:58
Comparative Study Between Q-NAS and Traditional CNNs for Brain Tumor Classificationaller than that found in the selected traditional architectures for this study. It shows the potential of the Q-NAS algorithm and highlights the importance of efficient model design in the context of accurate and feature-aware medical image analysis.lethal 发表于 2025-3-28 06:23:29
http://reply.papertrans.cn/33/3207/320623/320623_39.pngosteopath 发表于 2025-3-28 12:01:23
978-3-031-62494-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl