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Titlebook: Business Intelligence; 7th International Co Mohamed Fakir,Mohamed Baslam,Rachid El Ayachi Conference proceedings 2022 Springer Nature Switz

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樓主: 阿諛奉承
41#
發(fā)表于 2025-3-28 16:47:50 | 只看該作者
1865-1348 y were organized in topical sections as follows: decision support and artificial intelligence; business intelligence and database; and optimization and dynamic programming..978-3-031-06457-9978-3-031-06458-6Series ISSN 1865-1348 Series E-ISSN 1865-1356
42#
發(fā)表于 2025-3-28 21:36:41 | 只看該作者
https://doi.org/10.1007/978-3-642-54484-2ted and compared on the Intracranial Hemorrhage Dataset that contains 2814 images. The results show that the detection accuracy of Transfer Learning with Inception V3, which achieves 88.97%, is superior to that of the Convolutional neural network.
43#
發(fā)表于 2025-3-29 01:53:33 | 只看該作者
44#
發(fā)表于 2025-3-29 05:01:28 | 只看該作者
Mark Eisenegger,Mario Schranz,Angelo GislerCS-MC4 algorithms are presented. These algorithms are evaluated using Recall, precision and F-measure. Experimental results show that AD-Tree is faster and present higher accuracy than the other classifier using a Diabetes data set.
45#
發(fā)表于 2025-3-29 10:43:27 | 只看該作者
46#
發(fā)表于 2025-3-29 15:12:05 | 只看該作者
47#
發(fā)表于 2025-3-29 18:33:42 | 只看該作者
48#
發(fā)表于 2025-3-29 21:11:46 | 只看該作者
Facial Expression Recognition Using a?Hybrid ViT-CNN AggregatorN architecture when merged by different merging layers. The proposed approach is tested on the FER2013 and CK+ data sets. Experimental results demonstrate the high performance of the Average Merging Layer (AML), and our method outperforms state-of-the-art methods on FER2013 and CK+.
49#
發(fā)表于 2025-3-30 00:22:29 | 只看該作者
50#
發(fā)表于 2025-3-30 04:50:55 | 只看該作者
How far can Deep Learning Improve Arabic Part of Speech Tagging? develop POS taggers for the Arabic language. After multiple exclusion steps 12 articles were selected for a full review. Results show that Long Short-Term Memory (LSTM) and its extension Bidirectional LSTM (Bi-LSTM) models are the most used DL techniques for Arabic POS tagging, and they give better results according to the reviewed papers.
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