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Titlebook: Biomedical Engineering Systems and Technologies; 11th International J Alberto Cliquet Jr.,Sheldon Wiebe,Sergi Bermúdez i Conference proceed

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樓主: DEIFY
31#
發(fā)表于 2025-3-26 23:52:53 | 只看該作者
Going Deeper into Colorectal Cancer Histopathologyd from scratch obtained very good (about 90%) classification accuracy in our tests, the same CNN model pre-trained on the ImageNet dataset obtained even better accuracy (around 96%) on the same testing samples, requiring much lesser computational resources.
32#
發(fā)表于 2025-3-27 04:05:50 | 只看該作者
33#
發(fā)表于 2025-3-27 07:14:10 | 只看該作者
https://doi.org/10.1007/978-88-470-0597-6a quantitative assessment was performed using a validated usability assessment instrument, and, finally, in the third stage a focus group involving clinicians and usability experts was conducted. The results showed that SClínico presents important usability issues and, therefore, recommendations are suggested to overcome the identified issues.
34#
發(fā)表于 2025-3-27 09:46:55 | 只看該作者
35#
發(fā)表于 2025-3-27 16:14:18 | 只看該作者
Formal Neuron Models: Delays Offer a Simplified Dendritic Integration for Freeintegration into spiking neurons without explicit dendritic trees. This overcomes an explicit morphology representation and allows exploring many equivalent configurations via a single simplified model structure.
36#
發(fā)表于 2025-3-27 20:16:55 | 只看該作者
Considerations on the Usability of SClínicoa quantitative assessment was performed using a validated usability assessment instrument, and, finally, in the third stage a focus group involving clinicians and usability experts was conducted. The results showed that SClínico presents important usability issues and, therefore, recommendations are suggested to overcome the identified issues.
37#
發(fā)表于 2025-3-28 00:15:55 | 只看該作者
38#
發(fā)表于 2025-3-28 02:50:24 | 只看該作者
39#
發(fā)表于 2025-3-28 06:38:40 | 只看該作者
,Anatomia dell’apparato respiratorio,onal neural networks, a novel classification method on image level (based on a pre-trained Inception V.3 network with dedicated preprocessing and interpretation of class activation maps) is proposed and evaluated..The newly presented approach improves recognition performance, yielding accuracies of
40#
發(fā)表于 2025-3-28 14:20:59 | 只看該作者
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