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Titlebook: 13th International Conference on Information Systems and Advanced Technologies “ICISAT 2023”; New Trends in Artifi Mohamed Ridda Laouar,Val

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发表于 2025-3-21 17:02:42 | 显示全部楼层 |阅读模式
期刊全称13th International Conference on Information Systems and Advanced Technologies “ICISAT 2023”
期刊简称New Trends in Artifi
影响因子2023Mohamed Ridda Laouar,Valentina Emilia Balas,Abbas
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发行地址Focuses on recent topics in Artificial Intelligence, Computing, and Decision Making.Presents emerging trends in intelligent computing and informatics.Covers proceedings of the 13th International Confe
学科分类Lecture Notes in Networks and Systems
图书封面Titlebook: 13th International Conference on Information Systems and Advanced Technologies “ICISAT 2023”; New Trends in Artifi Mohamed Ridda Laouar,Val
影响因子.This book covers the Proceedings of the 13th International Conference on Information Systems and Advanced Technologies “ICISAT’2023.” One of the evocative and valuable dimensions of this conference is the way it brings together researchers, scientists, academics, and engineers in the field from different countries and enables discussions and debate of relevant issues, challenges, opportunities, and research findings. .The ICISAT’2023 conference provided a forum for research and developments in the field of information systems and advanced technologies and new trends in developing information systems organizational aspects of their development and intelligent aspects of the final product. .The aim of the ICISAT’2023 is to report progress and development of methodologies, technologies, planning and implementation, tools, and standards in information systems, technologies, and sciences..ICISAT’2023 aims at addressing issues related to the intelligent information, data science, and decision support system, from multidisciplinary perspectives and to discuss the research, teaching, and professional practice in the field. .The book of ICISAT’2023 includes selected papers from the 13th In
Pindex Conference proceedings 2024
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https://doi.org/10.1007/978-3-663-12978-3tically extracts local and global features from the normalized image. Different convolutional neural network configurations are used for classification, and an experimental study was conducted to assess the efficacy of the proposed system for image classification on CIFAR-10, CIFAR-100, and STL-10.
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Aufgaben über Mittelwerte und Streuungsmasseon method, wherein segmentation of words is not used and the image is identified as a whole. To create this system, a preprocessing operation is applied to images of words or digits, which includes size normalization and the removal of diacritical marks and white spaces in columns and rows. The word
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Aufgaben über Häufigkeitsverteilungenraphy plays a pivotal role in improving patient outcomes. Deep learning techniques, particularly CNNs, have demonstrated remarkable success in medical image analysis. In this study, we investigate the application of Faster R-CNN with detectron2, a state-of-the-art object detection framework, for the
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Aufgaben über Zeitreihenanalyseigent transportation system (ITS) has recorded a remarkable success. Nevertheless, the complex nature of the ITS makes cyberattacks a major concern even with cryptographic techniques employed for authentication of users, as they cannot prevent attacks from authenticated users (insider attackers). To
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