Titlebook: Intelligent Sustainable Systems; Proceedings of ICISS Jennifer S. Raj,Ram Palanisamy,Yong Shi Conference proceedings 2022 The Editor(s) (if

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书目名称Intelligent Sustainable Systems影响因子(影响力)




书目名称Intelligent Sustainable Systems影响因子(影响力)学科排名




书目名称Intelligent Sustainable Systems网络公开度




书目名称Intelligent Sustainable Systems网络公开度学科排名




书目名称Intelligent Sustainable Systems被引频次




书目名称Intelligent Sustainable Systems被引频次学科排名




书目名称Intelligent Sustainable Systems年度引用




书目名称Intelligent Sustainable Systems年度引用学科排名




书目名称Intelligent Sustainable Systems读者反馈




书目名称Intelligent Sustainable Systems读者反馈学科排名

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Intelligent Sustainable Systems978-981-16-2422-3Series ISSN 2367-3370 Series E-ISSN 2367-3389

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Conference proceedings 2022e of Engineering and Technology, Tirunelveli, Tamil Nadu, India, during February 26–27, 2021. The book discusses the latest research works that discuss the tools, methodologies, practices, and applications of sustainable systems and computational intelligence methodologies. The book is beneficial for readers from both academia and industry..

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Conference proceedings 2022e of Engineering and Technology, Tirunelveli, Tamil Nadu, India, during February 26–27, 2021. The book discusses the latest research works that discuss the tools, methodologies, practices, and applications of sustainable systems and computational intelligence methodologies. The book is beneficial fo

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A Novel Leaf Fragment Dataset and ResNet for Small-Scale Image Analysis,show that despite the difficulties of recognizing patterns from small-scale images, it is likely to efficiently categorize seed types and plant species by properly deploying residual blocks in neural network models. Also, the applied ResNet was compared against ResNet-152 V2 on the 64 × 64 pixel imageset in terms of species classification.

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Weather Divergence of Season Through Regression Analytics,ll in 2020. An analysis of a dependent variable and independent variables is multilinear regression. Through this study of approach algorithms, the seasons can be distinguished depending on the visualization.

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