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Titlebook: Advancement of Science and Technology; AI, Machine Learnin Abeba Birhane,Fekadu Shewarega,Ahunim Abebe Ashete Conference proceedings 2025

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https://doi.org/10.1007/978-3-663-02531-3rtifacts through preprocessing, segmentation, and classification. Patching is used to extract the region of interest (ROI), while multi-thresholding is used for segmentation. The suggested models, including CNN-KNN, VGGNet-16, CNN-naïve Bayes, and CNN-SVM, were tested on a dataset of images from the
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Grundlagen der Struktur der Materie information in social media. From previous research, it is noted that a lot of work has been done for different languages; however, there is no work done for the Amharic language. This work aimed to develop the data and emotion classification models for Amharic social media text comments using deep
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Integralformen der Grundgleichungen,ce human-like responses in the education context. To conduct this analysis, the paper includes a comprehensive review of relevant studies and articles on the use of ChatGPT in education. Additionally, the paper presents an experimental model for automatic question generation that focuses on function
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,Strömungen kleiner Reynolds-Zahlen,ing massive amounts of data. Recommender systems are one way to utilize this generated big data. However, currently, Ethiopian Tourism Institutions do not have a system to manage tourist sites, analyze customer preferences and behavior, or filter based on their interests. Therefore, the purpose of t
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,Strömungen kleiner Reynolds-Zahlen,strength of infrastructures. The maximum dry density (MDD) and the optimum moisture content (OMC) are the compaction parameters that are determined from the Atterberg limit tests. For this relationship, around 252 soil samples are used to model the relationship between the compaction parameters and
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