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Titlebook: Applications of Artificial Intelligence and Neural Systems to Data Science; Anna Esposito,Marcos Faundez-Zanuy,Eros Pasero Book 2023 The E

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发表于 2025-3-21 17:58:29 | 显示全部楼层 |阅读模式
期刊全称Applications of Artificial Intelligence and Neural Systems to Data Science
影响因子2023Anna Esposito,Marcos Faundez-Zanuy,Eros Pasero
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发行地址Provides an overview on the current progresses in artificial intelligence and neural nets in data science.Discusses computational intelligence tools for supporting multidisciplinary aspects of data mi
学科分类Smart Innovation, Systems and Technologies
图书封面Titlebook: Applications of Artificial Intelligence and Neural Systems to Data Science;  Anna Esposito,Marcos Faundez-Zanuy,Eros Pasero Book 2023 The E
影响因子This book provides an overview on the current progresses in artificial intelligence and neural nets in data science. The book is reporting on intelligent algorithms and applications modeling, prediction, and recognition tasks and  many other application areas supporting complex multimodal systems to enhance and improve human–machine or human–human interactions. This field is broadly addressed by the scientific communities and has a strong commercial impact since investigates on the theoretical frameworks supporting the implementation  of sophisticated computational intelligence tools. Such tools will  support multidisciplinary aspects of data mining and data processing characterizing appropriate system reactions to human-machine interactional exchanges in interactive scenarios. The emotional issue has recently gained increasing attention for such complex systems due to its relevance in helping in the most common human tasks (like cognitive processes, perception, learning, communication, and even "rational" decision-making) and therefore improving the quality of life of the end users..
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发表于 2025-3-21 23:33:45 | 显示全部楼层
Leaky Echo State Network for Audio Classification in Construction Sites. After the description of the proposed approach, we provide some numerical results obtained on the recorded signals. The overall accuracy on the test set, after the integration of a majority voting approach, is up to 95.3%, comparable to other state-of-the-art machine learning methods demonstrating the effectiveness of the approach.
发表于 2025-3-22 01:28:38 | 显示全部楼层
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发表于 2025-3-22 08:13:22 | 显示全部楼层
Akteure: Typen, Interessen, Kooperationenion problem is that of maximizing the coalition competence by respecting a cost constraint. We describe some examples in order to clarify our contribution. We also propose a multi-objective approach where one will try to maximize competence and minimize cost. We compute the Pareto front and compare the results of the two approaches.
发表于 2025-3-22 12:08:28 | 显示全部楼层
Breast Cancer Localization and Classification in Mammograms Using YoloV5 on the INbreast dataset. The performance was encouraging, resulting in an mAP of 0.838 ± 0.042, a recall of 0.722 ± 0.096, and a precision of 0.917 ± 0.077, calculated using the five-fold CV. The recognition rate achieved with the transfer learning on full-field digital mammograms, encouraging future analysis on a proprietary dataset.
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发表于 2025-3-23 09:21:27 | 显示全部楼层
Graph Neural Networks for Topological Feature Extraction in ECG Classificationnamed graph isomorphism network for classifying the ECGs. On the PTB Diagnostics data set, we tested the three proposed techniques. According to the findings, the three proposed techniques are capable of making arrhythmia classification predictions with the accuracy of 99.38, 98.76, and 91.93%, respectively.
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