Classification Applications with Deep Lear...

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Beschreibung

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.

Zusammenfassung

Presents recent research in Classification Applications with Deep Learning and Machine Learning Technologies

Brings together outstanding research and recent developments in the broad areas of Deep Learning and Machine Learning

Written by experts in the field

Inhaltsverzeichnis

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.

Details

Erscheinungsjahr:	2022
Fachbereich:	Technik allgemein
Genre:	Mathematik , Medizin , Naturwissenschaften , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Inhalt:	viii 288 S. 34 s/w Illustr. 201 farbige Illustr. 288 p. 235 illus. 201 illus. in color.
ISBN-13:	9783031175756
ISBN-10:	3031175751
Sprache:	Englisch
Einband:	Gebunden
Redaktion:	Abualigah, Laith
Herausgeber:	Laith Abualigah
Auflage:	1st edition 2023
Hersteller:	Springer International Publishing
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße:	241 x 160 x 21 mm
Von/Mit:	Laith Abualigah
Erscheinungsdatum:	17.11.2022
Gewicht:	0,665 kg