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Titlebook: Deep Learning Theory and Applications; 5th International Co Ana Fred,Allel Hadjali,Carlo Sansone Conference proceedings 2024 The Editor(s)

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樓主: deduce
21#
發(fā)表于 2025-3-25 04:24:51 | 只看該作者
Eigenschaften der Generation Y,his task is achieved using different deep learning models, not all models work well for all classes and their instances. There is limited work in the use of ensemble methods for LiDAR point cloud analysis that finds the optimal model from a set of existing models. We propose a workflow for an ensemb
22#
發(fā)表于 2025-3-25 08:40:24 | 只看該作者
Deep Learning Theory and Applications978-3-031-66705-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
23#
發(fā)表于 2025-3-25 11:56:36 | 只看該作者
24#
發(fā)表于 2025-3-25 16:57:50 | 只看該作者
Conference proceedings 2024 DeLTA 2024, which took place in Dijon, France, during July 10-11, 2024.?..The 44 papers included in these proceedings were carefully reviewed and selected from a total of 70 submissions. They focus on topics such as deep learning and big data analytics; machine-learning and artificial intelligence, etc.?.
25#
發(fā)表于 2025-3-25 23:27:48 | 只看該作者
Zusammenfassung der Diskussionsformen,ed on the mean average error threshold. The study concludes by analysing the effectiveness of the encoder-decoder LSTM-based method in detecting over-temperature anomalies in historical plant data. The proposed approach allows operators to take preventive measures before any potential alarms by providing a 300-s forecast window.
26#
發(fā)表于 2025-3-26 02:48:04 | 只看該作者
27#
發(fā)表于 2025-3-26 07:02:56 | 只看該作者
28#
發(fā)表于 2025-3-26 11:35:48 | 只看該作者
Eigenschaften der Generation Y,features as the meta-learning model, . the gating function. We tested the workflow on the nuScenes dataset using two ensembles, . different sets of CNNs to compare their performance. Our experimental results show that the ensemble of models demonstrates the expected results of overall improved accuracy.
29#
發(fā)表于 2025-3-26 14:21:09 | 只看該作者
30#
發(fā)表于 2025-3-26 17:01:31 | 只看該作者
,Automating the?Conducting of?Surveys Using Large Language Models,he text to a Large Language Model (GPT-4) which is prompted to extract the responses. The responses are then uploaded to a database. Finally we use an LLM to provide answers to questions about the survey responses. For multiple choice questions we obtained an accuracy score of 97%.
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