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Titlebook: Artificial Intelligence Tools and Applications in Embedded and Mobile Systems; Selected Papers from Jorge Marx Gómez,Anael Elikana Sam,Devo

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Contextual Multi-View Graph Community Detection Using Graph Neural Networks,t consider only single-view features and neglect the context, are insufficient. Then in industrial cases, graphs often contain multiple views and the context surrounding the graph may influence the community preference for vertices..To address this challenging problem, we introduce Contextual Graph
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,Feature Selection Approach to Improve Malaria Prediction Model’s Performance for High- and Low-Endesifier, a tree-based, was used to select the most important features for malaria prediction since this classifier was selected for feature selection because it was robust and had high performance. Regional-based features were obtained to facilitate accurate prediction. The feature ranking indicated
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Object Detection Model for Poultry Diseases Diagnostics,n of all four classes of the dataset. Model performance during training was evaluated based on the following metrics: precision, recall, and mean average precision with IOU (Intersection Over Union) of 0.5 (mAP_0.5). The best training results were obtained at epoch 506. The model was deployed on a w
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Machine Learning Model for Predicting Construction Project Success in Tanzania,to identify factors influencing construction project success. Generative Adversarial Networks (GANs) were used to expand the dataset to 1082. The model was developed, trained, and tested. The model had an accuracy of 97.5% and was deployed in a web-based application. The contribution of this study i
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Determining Emotion Intensities from Audio Data Using a Convolutional Neural Network,nformation in the form of observations and real-world interactions. A multi-modal approach comprising several machine learning algorithms is required to map out the intensities contained in the emotion classes. Mel Frequency Cepstral Coefficients are a set of about 10–20 features obtained from a spe
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