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Titlebook: Communications, Signal Processing, and Systems; Proceedings of the 2 Qilian Liang,Xin Liu,Baoju Zhang Conference proceedings 2020 Springer

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樓主: 貪吃的人
21#
發(fā)表于 2025-3-25 03:45:13 | 只看該作者
22#
發(fā)表于 2025-3-25 10:43:28 | 只看該作者
23#
發(fā)表于 2025-3-25 14:45:13 | 只看該作者
24#
發(fā)表于 2025-3-25 17:34:53 | 只看該作者
DEEP: Detection of Environmental Pollution Using Cooperative Neural Networkccelerate the convergence of the algorithm and also can enhance the precision. Simulation results demonstrate that the proposed method outperforms conventional schemes in terms of environmental pollution detection accuracy, as well as monitoring different pollutants.
25#
發(fā)表于 2025-3-25 21:08:04 | 只看該作者
Improved Efficient Dictionary Learning with Cross-Label and Group Regularizationuals generated when reconstructing signals with the learnt dictionary sparse codes. Demonstrated by the results of experiments, the proposed method intends to determine a more reasonable sparse dimension, which can not only obtain desired classification results but also decrease much of the redundancy in experimental computation.
26#
發(fā)表于 2025-3-26 03:31:27 | 只看該作者
Multi-task Cascaded Convolutional Neural Networks for Real-Time Dynamic Face Recognition Methodnces directly correspond to a measure of face similarity to extract the performance of facial feature algorithms. In the practical application scenario, we set up a multi-camera real-time monitoring system to perform face matching and recognition of collected continuous frames from different angles in real time.
27#
發(fā)表于 2025-3-26 06:05:03 | 只看該作者
Research on Fault Diagnosis Based on Artificial Neural Networkh various methods are introduced, and the research progress and typical applications of the neural network in fault diagnosis are given. The existing problems and future development directions of fault diagnosis are also discussed.
28#
發(fā)表于 2025-3-26 11:11:39 | 只看該作者
29#
發(fā)表于 2025-3-26 14:38:37 | 只看該作者
30#
發(fā)表于 2025-3-26 17:49:17 | 只看該作者
1876-1100 undergraduate and graduate electrical engineering, computer science and mathematics students, researchers and engineers from academia and industry as well as government employees..978-981-13-6510-2978-981-13-6508-9Series ISSN 1876-1100 Series E-ISSN 1876-1119
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