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Titlebook: Soft Computing: Biomedical and Related Applications; Nguyen Hoang Phuong,Vladik Kreinovich Book 2021 The Editor(s) (if applicable) and The

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樓主: GLAZE
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發(fā)表于 2025-3-23 13:26:09 | 只看該作者
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發(fā)表于 2025-3-23 16:46:32 | 只看該作者
End-to-End Hand Rehabilitation System with Single-Shot Gesture Classification for Stroke Patientsxplored and found unmatured, expensive and uncomfortable. Existing devices to assist rehabilitation are typically costly, bulky and difficult to set up. Our proposed solution aims to provide an end-to-end hand rehabilitation system that can be produced at low cost with greater ease of use. It incorp
13#
發(fā)表于 2025-3-23 21:50:20 | 只看該作者
Feature Selection Based on Shapley Additive Explanations on Metagenomic Data for Colorectal Cancer Dd to personalized medicine approaches usually consider metagenomic data as a valuable data source for developing and proposing methods for disease treatments. We usually face challenges for processing metagenomic data because of its high dimensionality and complexities. Numerous studies have attempt
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發(fā)表于 2025-3-23 22:57:39 | 只看該作者
Clinical Decision Support Systems for Pneumonia Diagnosis Using Gradient-Weighted Class Activation Mplied to Chest X-Ray (CXR) images for disease diagnosis. Numerous scientists have attempted to develop efficient image-based diagnosis methods using DL algorithms. Their proposed methods can yield very reasonable performance on prediction tasks, but it is very hard to interpret the generated output
15#
發(fā)表于 2025-3-24 06:15:25 | 只看該作者
Improving 3D Hand Pose Estimation with Synthetic RGB Image Enhancement Using RetinexNet and Dehazingrent state of research does present some opportunities for improvement of estimation accuracy. This paper presents several image enhancement techniques to embed with existing deep learning architectures to improve the performance of hand pose estimation. In particular, we propose a preprocessing app
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發(fā)表于 2025-3-24 07:08:02 | 只看該作者
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發(fā)表于 2025-3-24 11:37:35 | 只看該作者
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發(fā)表于 2025-3-24 15:37:18 | 只看該作者
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發(fā)表于 2025-3-24 19:55:10 | 只看該作者
Fine-Grained Network Traffic Classification Using Machine Learning: Evaluation and Comparisonresearchers have successfully applied machine learning techniques to solve the coarse-grained traffic classification problem with very high accuracy. However, there are few studies associated with the fine-grained traffic classification problem because of an appropriate lack of labeled data of the a
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發(fā)表于 2025-3-24 23:32:42 | 只看該作者
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