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Classification applications with dee...

Abualigah, Laith.

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Classification applications with deep learning and machine learning technologies

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Classification applications with deep learning and machine learning technologies/ edited by Laith Abualigah.
其他作者:	Abualigah, Laith.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	viii, 288 p. :ill., digital ;24 cm.
內容註:	Artocarpus Classification Technique using Deep Learning based Convolutional Neural Network -- Rambutan Image Classification using Various Deep Learning Approaches -- Mango Varieties Classification-based Optimization with Transfer Learning and Deep Learning Approaches -- Salak Image Classification Method based Deep Learning Technique using Two Transfer Learning Models -- Image Processing Identification for Sapodilla Using Convolution Neural Network (CNN) and Transfer Learning Techniques -- Comparison of Pre-trained and Convolutional Neural Networks for Classification of Jackfruit Artocarpus Integer and Artocarpus Heterophyllus -- Markisa/Passion Fruit Image Classification based Improved Deep Learning Approach using Transfer Learning -- Enhanced MapReduce Performance for the Distributed Parallel Computing: Application of the Big Data -- A Novel Big Data Classification Technique for Healthcare Application using Support Vector Machine, Random Forest and J48 -- Comparative Study on Arabic Text Classification: Challenges and Opportunities -- Pedestrian Speed Prediction Using Feed Forward Neural Network -- Arabic Text Classification using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect.
Contained By:	Springer Nature eBook
標題:	Machine learning. -
電子資源:	https://doi.org/10.1007/978-3-031-17576-3
ISBN:	9783031175763

Classification applications with deep learning and machine learning technologies
Classification applications with deep learning and machine learning technologies[electronic resource] /edited by Laith Abualigah. - Cham :Springer International Publishing :2023. - viii, 288 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 10711860-9503 ;. - Studies in computational intelligence ;v. 1071..

Artocarpus Classification Technique using Deep Learning based Convolutional Neural Network -- Rambutan Image Classification using Various Deep Learning Approaches -- Mango Varieties Classification-based Optimization with Transfer Learning and Deep Learning Approaches -- Salak Image Classification Method based Deep Learning Technique using Two Transfer Learning Models -- Image Processing Identification for Sapodilla Using Convolution Neural Network (CNN) and Transfer Learning Techniques -- Comparison of Pre-trained and Convolutional Neural Networks for Classification of Jackfruit Artocarpus Integer and Artocarpus Heterophyllus -- Markisa/Passion Fruit Image Classification based Improved Deep Learning Approach using Transfer Learning -- Enhanced MapReduce Performance for the Distributed Parallel Computing: Application of the Big Data -- A Novel Big Data Classification Technique for Healthcare Application using Support Vector Machine, Random Forest and J48 -- Comparative Study on Arabic Text Classification: Challenges and Opportunities -- Pedestrian Speed Prediction Using Feed Forward Neural Network -- Arabic Text Classification using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect.

This book is very beneficial for early researchers/faculty who want to work in deep learning and machine learning for the classification domain. It helps them study, formulate, and design their research goal by aligning the latest technologies studies' image and data classifications. The early start-up can use it to work with product or prototype design requirement analysis and its design and development.

ISBN: 9783031175763

Standard No.: 10.1007/978-3-031-17576-3doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Classification applications with deep learning and machine learning technologies
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520 $a This book is very beneficial for early researchers/faculty who want to work in deep learning and machine learning for the classification domain. It helps them study, formulate, and design their research goal by aligning the latest technologies studies' image and data classifications. The early start-up can use it to work with product or prototype design requirement analysis and its design and development.
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