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Titlebook: Information and Communication Technologies; 11th Ecuadorian Conf Jorge Maldonado-Mahauad,Jorge Herrera-Tapia,Santia Conference proceedings

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發(fā)表于 2025-3-21 18:00:16 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Information and Communication Technologies
副標(biāo)題11th Ecuadorian Conf
編輯Jorge Maldonado-Mahauad,Jorge Herrera-Tapia,Santia
視頻videohttp://file.papertrans.cn/466/465791/465791.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Information and Communication Technologies; 11th Ecuadorian Conf Jorge Maldonado-Mahauad,Jorge Herrera-Tapia,Santia Conference proceedings
描述This book constitutes the proceedings of the 11th Ecuadorian Conference on Information and Communication Technologies, TICEC 2023, held in Cuenca, Ecuador, during October 18–20, 2023..The 31 full papers presented were carefully reviewed and selected from 120 submissions. The papers cover a great variety of topics, such as internet of things, cyber-physical systems, human-machine interface, artificial Intelligence, e-Learning, smart healthcare, smart healthcare and others.?.The papers are organized in the following topical sections: data science and machine learning; ICTs and their applications; and software development..
出版日期Conference proceedings 2023
關(guān)鍵詞artificial intelligence; clustering algorithms; computer networks; computer security; computer vision; co
版次1
doihttps://doi.org/10.1007/978-3-031-45438-7
isbn_softcover978-3-031-45437-0
isbn_ebook978-3-031-45438-7Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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書目名稱Information and Communication Technologies影響因子(影響力)




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Machine Learning Applied to?the?Analysis of?Glacier Massesn having a substantial effect on glacier mass balance, as confirmed by the forecast results. This study emphasizes the importance of machine learning to improve our understanding of glacier dynamics and support informed decision-making in the face of climate change. Collecting additional specific da
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Profit vs Accuracy: Balancing the?Impact on?Users Introduced by?Profit-Aware Recommender Systemse-ranked. Experiments showed that MARS models have the ability to control the impact on the user while increasing the profit by varying the weights associated to the considered attributes. It is important to notice that the training of the model can be parallelized; thus, the weights and results may
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Augmenting Data with?DCGANs to?Improve Skin Lesions Classificationt to improve the final performance of the classification network for skin lesions. The achieved results were compared with the classification of the original data. They showed that the augmentation of images generated by the DCGAN improves the network’s performance for the classification task.
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Unraveling the?Power of?4D Residual Blocks and?Transfer Learning in?Violence Detectionetter feature propagation and improved performance. In this work, we propose using 4D residual blocks and MoViNets for violence detection on the data set RWF-2000 to achieve state-of-the-art results in action recognition. Furthermore, this approach compares the strengths of MoViNet and V4D, resultin
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Advanced Metrics to Evaluate Autistic Children’s Attention and Emotions from Facial Characteristics assical observational techniques. Part of the analysis will also consist of comparing the results of the videos taken from different reference points of the robot, such as from the head and bust. As a result of the trial-error follow-up, the comparative analysis between automatic and observational t
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Performance Analysis of You Only Look Once, RetinaNet, and Single Shot Detector Applied to Vehicle Dlts indicated that YOLOv8 (which has undergone the most adjustments since its inception) exhibits the best performance in terms of detection time, precision considering the frames that need to be analyzed to enable real-time usage, and ease of implementation.
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