Recent advancements in imaging techniques and image analysis has broadened the horizons for their applications in various domains. Image analysis has become an influential technique in medical image analysis, optical character recognition, geology, remote sensing, and more. However, analysis of images under constrained and unconstrained environments require efficient representation of the data and complex models for accurate interpretation and classification of data. Deep learning methods, with their hierarchical/multilayered architecture, allow the systems to learn complex mathematical models to provide improved performance in the required task. The Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. Highlighting concepts, methods, and tools including convolutional neural networks, edge enhancement, image segmentation, machine learning, and image processing, the book is an essential and comprehensive reference work for engineers, academicians, researchers, and students.
"Sinopsis" puede pertenecer a otra edición de este libro.
Vijayalakshmi G. V. Mahesh received her BE in Electronics and Communication Engineering from Bangalore University, India in 1999, and M.Tech in Digital Communication and Networking from Visvesvaraya Technological University in 2005 and the Ph.D. degree from the Vellore Institute of Technology, Vellore, India. Currently she is working as an Associate Professor at BMS Institute of Technology and Management, Bangalore, India. She has been in academics for over 19 years and has published her research in various reputed journals and conferences. Dr. Vijayalakshmi is serving as academic editor for various journals. She has edited and published two books " Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments" and " Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks" with IGI Global publishers. Her research interests include Machine Learning, Image Processing, Pattern Recognition and Deep learning, Affective computing.
"Sobre este título" puede pertenecer a otra edición de este libro.
EUR 31,19 gastos de envío desde Reino Unido a España
Destinos, gastos y plazos de envíoEUR 5,19 gastos de envío desde Reino Unido a España
Destinos, gastos y plazos de envíoLibrería: dsmbooks, Liverpool, Reino Unido
hardcover. Condición: Very Good. Very Good. book. Nº de ref. del artículo: D7S9-1-M-1799866904-5
Cantidad disponible: 1 disponibles
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9781799866909_new
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9781799866909
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9781799866909
Cantidad disponible: Más de 20 disponibles
Librería: moluna, Greven, Alemania
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. The book highlight concepts, methods, and tools, including convolutional neura. Nº de ref. del artículo: 448342868
Cantidad disponible: Más de 20 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recent advancements in imaging techniques and image analysis has broadened the horizons for their applications in various domains. Image analysis has become an influential technique in medical image analysis, optical character recognition, geology, remote sensing, and more. However, analysis of images under constrained and unconstrained environments require efficient representation of the data and complex models for accurate interpretation and classification of data. Deep learning methods, with their hierarchical/multilayered architecture, allow the systems to learn complex mathematical models to provide improved performance in the required task. The Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. Highlighting concepts, methods, and tools including convolutional neural networks, edge enhancement, image segmentation, machine learning, and image processing, the book is an essential and comprehensive reference work for engineers, academicians, researchers, and students. Nº de ref. del artículo: 9781799866909
Cantidad disponible: 1 disponibles