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Titlebook: Artificial Intelligence and Soft Computing; 18th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2019

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樓主: Goiter
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發(fā)表于 2025-3-28 16:31:49 | 只看該作者
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發(fā)表于 2025-3-29 00:00:38 | 只看該作者
Application of Spiking Neural Networks to Fashion Classification The main difference between them and previous generation networks is that they are based on spiking neurons. This approach leads us to the need of using specific ways of coding inputs and outputs as well as original methods of learning. The paper considers evaluation of such a network with a Fashio
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發(fā)表于 2025-3-29 05:52:02 | 只看該作者
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發(fā)表于 2025-3-29 10:16:30 | 只看該作者
0302-9743 ics, biometrics, and medical applications; data mining; various problems of artificial intelligence; agent systems, robotics and control..978-3-030-20911-7978-3-030-20912-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
46#
發(fā)表于 2025-3-29 15:12:58 | 只看該作者
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發(fā)表于 2025-3-29 16:00:19 | 只看該作者
Der Instanzenzug im Zivilprozessnt of calculations inside the control loop - which with proper tuning have no negative impact on the controller’s performance. The proposed approach outperforms the multi-input Proportional-Derivative (PD) controller preoptimized using a genetic algorithm.
48#
發(fā)表于 2025-3-29 23:33:20 | 只看該作者
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發(fā)表于 2025-3-30 00:28:29 | 只看該作者
Smart Well Data Generation via Boundary-Seeking Deep Convolutional Generative Adversarial Networksd to diversify existing data as to improve lacking datasets, and data privacy, as the generated data, while next to real, can be shared without the original, protected model. A case study was done in an industry-recognized benchmark model, and the results completely support the use of the proposed m
50#
發(fā)表于 2025-3-30 05:44:38 | 只看該作者
Neural Net Model Predictive Controller for Adaptive Active Vibration Suppression of an Unknown Systent of calculations inside the control loop - which with proper tuning have no negative impact on the controller’s performance. The proposed approach outperforms the multi-input Proportional-Derivative (PD) controller preoptimized using a genetic algorithm.
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