迅速飞过 发表于 2025-3-23 12:28:08
http://reply.papertrans.cn/99/9811/981046/981046_11.pngpulse-pressure 发表于 2025-3-23 17:55:11
http://reply.papertrans.cn/99/9811/981046/981046_12.pngcinder 发表于 2025-3-23 19:34:39
chine learning-based strategies have been proposed to detect phishing websites. These techniques utilize a set of features extracted from website samples, the structure and syntax of URLs, the content of the pages, and querying external resources. In this work, we use a dataset of 11,430 samples wit协议 发表于 2025-3-23 23:41:18
ous values, enabling a better understanding of the temporal dynamics of gait. First of all, data from seven participants were collected using a gadget with an Arduino Nano 33 IoT attached to their feet. Performance evaluation was conducted using metrics, such as accuracy, precision, recall, and F1 sTincture 发表于 2025-3-24 03:21:36
Lin Zhangde evidence of the predictive capability of the proposed method. The neural network with variables selected via the first principal component analysis obtained out of sample errors of that were approximately 15.4% lower than the neural nets with input variables selected by correlation analysis. In a颠簸地移动 发表于 2025-3-24 08:57:29
Lin Zhangthe mentioned deficiencies via (1) restricting the number of links that can impact the pagerank (2) allowing for multistep linkage to be taken into account. The preliminary experiments on a large scale search engine data confirm the value of this new approach.下船 发表于 2025-3-24 11:00:09
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http://reply.papertrans.cn/99/9811/981046/981046_18.pngAlbinism 发表于 2025-3-24 20:45:42
Lin Zhang and Simulation, Various Problems of Artificial Intelligence, Special Session 2: Machine Learning for Visual Information Analysis and Security, Special Session 1: Applications and Properties of Fuzzy Reasoning and Calculus and Clustering.978-3-319-07175-6978-3-319-07176-3Series ISSN 0302-9743 Series E-ISSN 1611-3349sclera 发表于 2025-3-24 23:09:35
Lin Zhang even with small datasets. Multivariate datasets can only benefit from the adversarial domain adaptation if the number of data points is large enough. VRADA was found to outperform CoDATS in modeling multivariate datasets. The multisource training available in CoDATS appears promising. A correlation