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Titlebook: Advances in System-Integrated Intelligence; Proceedings of the 6 Maurizio Valle,Dirk Lehmhus,Klaus-Dieter Thoben Conference proceedings 202

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樓主: Nixon
11#
發(fā)表于 2025-3-23 11:57:04 | 只看該作者
Towards a?Trade-off Between Accuracy and?Computational Cost for?Embedded Systems: A Tactile Sensing nt algorithms. Results show that the best performance, when the computational cost is not relevant, is achieved by the fully–connected neural network using 16 features, while, when the computational cost matters, the loss function showed that the kernel SVM with 4 features has the best performance.
12#
發(fā)表于 2025-3-23 16:34:09 | 只看該作者
13#
發(fā)表于 2025-3-23 21:27:17 | 只看該作者
David B. Mertz,David E. McCauleyystem is not available or too complex. The proposed approach is currently under evaluation in the water distribution system of the Milan (Italy) water main. The application of the approach to synthetic data shows its ability of reducing the energy consumption, while ensuring a good quality of service.
14#
發(fā)表于 2025-3-24 01:12:08 | 只看該作者
15#
發(fā)表于 2025-3-24 02:43:26 | 只看該作者
16#
發(fā)表于 2025-3-24 07:08:20 | 只看該作者
Machine Learning Based Reconstruction of Process Forcesches show different results depending on the milling center. Only for the LSTM an error lower than 30?N is achieved for both machine tools. Independent of the ML approach, the results strongly depend on the selection of milling processes used for training.
17#
發(fā)表于 2025-3-24 12:48:20 | 只看該作者
18#
發(fā)表于 2025-3-24 15:56:13 | 只看該作者
An Optimized Heart Rate Detection System Based on?Low-Power Microcontroller Platforms for?Biosignal ed on the RISC-V PULP platform. Experimental results show that our approach achieves an accuracy above 99.5%, comparable to the state-of-the-art solutions, and an energy efficiency that is one order of magnitude better than other software solutions.
19#
發(fā)表于 2025-3-24 19:04:48 | 只看該作者
https://doi.org/10.1007/978-3-030-78803-2actors, as well as the implementation of an object recognition, are investigated. The following paper addresses the question of the extent to which manual assembly processes can be reliably derived from visual sensor data and classified by machine learning algorithms.
20#
發(fā)表于 2025-3-24 23:19:45 | 只看該作者
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