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Titlebook: Artificial Intelligence and Soft Computing; 21st International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2023

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樓主: aspirant
11#
發(fā)表于 2025-3-23 10:22:07 | 只看該作者
K. Biesalski,H. Eckhardt,K. Wickelearch experiment we have examined also other latest algorithms to select the best configuration of proposed model. Results show that our proposed BiLSTM deep learning neural network archived over 99% of accuracy.
12#
發(fā)表于 2025-3-23 15:21:16 | 只看該作者
13#
發(fā)表于 2025-3-23 19:20:17 | 只看該作者
14#
發(fā)表于 2025-3-24 00:38:30 | 只看該作者
15#
發(fā)表于 2025-3-24 04:55:37 | 只看該作者
16#
發(fā)表于 2025-3-24 07:38:19 | 只看該作者
Training Subjective Perception Biased Images of?Vehicle Ambient Lights with?Deep Belief Networks Usiof the contrastive divergence pre-training is analyzed on the accuracy of the trained networks. The results are promising for decision support in the production process to minimize the influence of subjectivity by human evaluators.
17#
發(fā)表于 2025-3-24 14:27:18 | 只看該作者
18#
發(fā)表于 2025-3-24 15:38:49 | 只看該作者
Analysis and?Detection of?DDoS Backscatter Using NetFlow Data, Hyperband-Optimised Deep Learning andke. In the following work, an analysis of the detection of DDoS Backscatter with the use of neural networks is performed. To this end, a novel dataset is collected and described, on which a hyperband-optimized neural network is trained, and the decision process of the classifier is explained using LIME and SHAP.
19#
發(fā)表于 2025-3-24 20:50:54 | 只看該作者
BiLSTM Deep Learning Model for?Heart Problems Detectionearch experiment we have examined also other latest algorithms to select the best configuration of proposed model. Results show that our proposed BiLSTM deep learning neural network archived over 99% of accuracy.
20#
發(fā)表于 2025-3-25 00:01:47 | 只看該作者
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