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Titlebook: Breath Analysis for Medical Applications; David Zhang,Dongmin Guo,Ke Yan Book 2017 Springer Nature Singapore Pte Ltd. 2017 Breath signal D

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樓主: 萌芽的心
51#
發(fā)表于 2025-3-30 10:41:21 | 只看該作者
52#
發(fā)表于 2025-3-30 14:23:18 | 只看該作者
https://doi.org/10.1007/978-3-322-87042-1 the responses of all the sensors in the system, and . can be regarded as the weight vectors for these sensors which indicate the contribution weight of each sensor. Accordingly, it is possible to determine which sensor has a greater contribution in classifying the two classes. A series of experimen
53#
發(fā)表于 2025-3-30 17:17:13 | 只看該作者
https://doi.org/10.1007/978-3-031-11637-7s are adopted to collect a dataset, which contains pure chemicals and breath samples. Experiments show that WPDS outperforms previous methods in the sense of standardization error and prediction accuracy; SEMI consistently enhances the accuracy of the master model applied to standardized slave data.
54#
發(fā)表于 2025-3-30 22:24:30 | 只看該作者
Ikujiro Nonaka,Ichiro Yamaguchil feature-level drift correction algorithms and typical labeled-sample-based MTL methods, with few transfer samples needed. TMTL is a practical algorithm framework which can greatly enhance the robustness of sensor systems with complex drift.
55#
發(fā)表于 2025-3-31 03:01:30 | 只看該作者
56#
發(fā)表于 2025-3-31 08:27:28 | 只看該作者
Unternehmer sind die besseren Mathematiker, and “not controlled”, respectively. The experimental results show that the accuracy to classify the diabetes samples can be up?to 68.66%. The current prediction correct rates are not quite high, but the results are promising because it provides a possibility of noninvasive blood glucose measurement
57#
發(fā)表于 2025-3-31 10:09:46 | 只看該作者
58#
發(fā)表于 2025-3-31 16:51:27 | 只看該作者
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