Titlebook: Advances in Intelligent Computing Techniques and Applications; Intelligent Systems, Faisal Saeed,Fathey Mohammed,Yousef Fazea Conference pr

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书目名称Advances in Intelligent Computing Techniques and Applications影响因子(影响力)




书目名称Advances in Intelligent Computing Techniques and Applications影响因子(影响力)学科排名




书目名称Advances in Intelligent Computing Techniques and Applications网络公开度




书目名称Advances in Intelligent Computing Techniques and Applications网络公开度学科排名




书目名称Advances in Intelligent Computing Techniques and Applications被引频次




书目名称Advances in Intelligent Computing Techniques and Applications被引频次学科排名




书目名称Advances in Intelligent Computing Techniques and Applications年度引用




书目名称Advances in Intelligent Computing Techniques and Applications年度引用学科排名




书目名称Advances in Intelligent Computing Techniques and Applications读者反馈




书目名称Advances in Intelligent Computing Techniques and Applications读者反馈学科排名

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Lecture Notes on Data Engineering and Communications Technologieshttp://image.papertrans.cn/b/image/167278.jpg

调色板

Advances in Intelligent Computing Techniques and Applications978-3-031-59711-4Series ISSN 2367-4512 Series E-ISSN 2367-4520

会议

Polarisation und Haftintensitätiversally applicable guidelines for machine learning and deep learning practitioners to use when evaluating health information. This study seeks to address the gap by empirically identifying a set of tangible guidelines for assessing health information. Drawing from existing literature, we identifie

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Die Reduktions- und Oxydationskettenenue Prediction dataset as a case study. The dataset contains anonymized data from the Google Merchandise Store, an e-commerce site that sells Google-branded merchandise. We use the data to build and evaluate different machine learning models that predict the natural log of the revenue per customer

peak-flow

Die Überführungszahlen von Hittorfatient care. In this study, we present a comprehensive analysis of brain tumor classification using a multi-modal MRI dataset comprising 17 distinct tumor classes. The dataset is split into training (60%), validation (20%), and testing (20%) sets, ensuring a robust evaluation of our proposed approac

AVOW

https://doi.org/10.1007/978-3-662-25666-4 number of such studies is relatively limited compared to those conducted on English or other Latin languages, indicating a research gap. In this paper, we propose a new approach to ASA based on the comments dataset of users of mobile applications available on the Google play store. The proposed app