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Titlebook: Advances in Artificial Intelligence and Machine Learning in Big Data Processing; First International R. Geetha,Nhu-Ngoc Dao,Saeed Khalid C

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41#
發(fā)表于 2025-3-28 18:38:14 | 只看該作者
42#
發(fā)表于 2025-3-28 22:45:09 | 只看該作者
https://doi.org/10.1007/978-3-540-74773-4current challenges and future prospects in deep learning-driven research for HAR, including the need for improved interpretability, adaptability to novel activities and settings, and integration of multiple modalities to advance HAR. In summary, this review provides valuable insights into DL-driven
43#
發(fā)表于 2025-3-28 23:56:31 | 只看該作者
https://doi.org/10.1007/978-3-540-74773-4ghts, weights, and gender of the training images. After the image is passed into the network, it generates BMI, age, and gender predictions for the input image. This system uses an efficient face recognition mechanism to identify the age, gender, and BMI of a person using a multi-task BMI prediction
44#
發(fā)表于 2025-3-29 05:23:18 | 只看該作者
Grundlagen der Wirtschaftspolitikm benign files. In the presented PSODL-IC technique, the noise elimination stage employs Gaussian filtration (GF). In addition, the presented PSODL-IC method employs the Xception feature extractor in conjunction with a PSO-based hyperparameter optimizer. In this investigation, the auto encoder (AE)
45#
發(fā)表于 2025-3-29 07:53:27 | 只看該作者
https://doi.org/10.1007/978-3-7091-3494-8s of 30K phishing URLs and 60K legitimate URLs, including login and index pages. The latest model we propose accomplishes 96.50% exactness on the introduced login URL dataset when Calculated Relapse matched with Term Recurrence - Backwards Record Recurrence (TF-IDF) include extraction.
46#
發(fā)表于 2025-3-29 13:27:56 | 只看該作者
47#
發(fā)表于 2025-3-29 18:30:22 | 只看該作者
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發(fā)表于 2025-3-29 21:23:05 | 只看該作者
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發(fā)表于 2025-3-30 01:10:27 | 只看該作者
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發(fā)表于 2025-3-30 04:59:48 | 只看該作者
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