Artículos relacionados a Advances in Vision Foundation Models, Recognition,...
Sinopsis
Computer vision has undergone a profound transformation over the past decade, initially driven by deep convolutional neural networks and more recently by the emergence of large-scale Vision Foundation Models (VFMs). Inspired by the success of foundation models in natural language processing, approaches such as Vision Transformers (ViTs), multimodal models, and self-supervised architectures have redefined how visual understanding systems are designed, trained, and deployed. Pre-trained on massive datasets and adaptable to a wide range of downstream tasks, these models are reshaping both research and industry. From image classification and object detection to multimodal reasoning, medical imaging, autonomous systems, and intelligent surveillance, foundation-based vision systems are enabling scalable, transferable, and data-efficient solutions. Advances in Vision Foundation Models, Recognition, and Practical Systems presents a comprehensive and up-to-date exploration of developments in vision foundation models, recognition techniques, and real-world system deployment. By bridging theoretical foundations, architectural innovations, training paradigms, and practical applications, this book balances cutting-edge research insights with implementation-oriented guidance, making it both academically rigorous and highly relevant to industry. Covering topics such as adversarial robustness, scalable object recognition, and vision foundation models, this book is an excellent academic resource for graduate and doctoral students, AI engineers, computer vision practitioners, data scientists, software developers, system architects, and more.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca de los autores
Jamal Zraqou is an associate professor at the Department of Computer Science/Virtual and Augmented Reality, University of Petra, Jordan, where he has been a faculty member since 2022. From 2018-2029, he was also the dean faculty of IT at IU. His research interests include computer vision, virtual and augmented reality, internet of things (IoT), cyber security, and image processing. He can be contacted at email: Jamal.Zraqou@uop.edu.jo.
Jawad Alkhateeb is currently working as an Assistant Professor at Prince Mohammad Bin Fahd University, Kingdom of Saudi Arabia in the College of Computer Engineering and Science, Department of computer Engineering. Dr. Alkhateeb received his PhD degree in Computer Engineering - Artificial Intelligence from the University of Bradford, UK in 2010. He Received his MSc and BSc degrees in Electrical and Computer Engineering from Louisiana Tech University, Ruston, USA in 1992 and 1991 respectively. He has a 30-year academic experience in teaching Computer Science and Engineering topics and in conducting research related to Artificial Intelligence, Pattern Recognition, Machine Learning, Deep Learning, Arabic OCR, and IoT.
"Sobre este título" puede pertenecer a otra edición de este libro.
Resultados de la búsqueda para Advances in Vision Foundation Models, Recognition,...
Imagen de archivo
Advances in Vision Foundation Models, Recognition, and Practical Systems
Impresión bajo demandaLibrería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9798260001363
Comprar nuevo
EUR 243,36
Gastos de envío gratis
Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Advances in Vision Foundation Models, Recognition, and Practical Systems
Impresión bajo demandaLibrería: PBShop.store UK, Fairford, GLOS, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
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: L1-9798260001363
Comprar nuevo
EUR 233,48
Envío por EUR 11,19
Se envía de Reino Unido a Estados Unidos de America
Se envía de Reino Unido a Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Advances in Vision Foundation Models, Recognition, and Practical Systems (Hardcover)
Impresión bajo demandaLibrería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: new. Hardcover. Computer vision has undergone a profound transformation over the past decade, initially driven by deep convolutional neural networks and more recently by the emergence of large-scale Vision Foundation Models (VFMs). Inspired by the success of foundation models in natural language processing, approaches such as Vision Transformers (ViTs), multimodal models, and self-supervised architectures have redefined how visual understanding systems are designed, trained, and deployed. Pre-trained on massive datasets and adaptable to a wide range of downstream tasks, these models are reshaping both research and industry. From image classification and object detection to multimodal reasoning, medical imaging, autonomous systems, and intelligent surveillance, foundation-based vision systems are enabling scalable, transferable, and data-efficient solutions. Advances in Vision Foundation Models, Recognition, and Practical Systems presents a comprehensive and up-to-date exploration of developments in vision foundation models, recognition techniques, and real-world system deployment. By bridging theoretical foundations, architectural innovations, training paradigms, and practical applications, this book balances cutting-edge research insights with implementation-oriented guidance, making it both academically rigorous and highly relevant to industry. Covering topics such as adversarial robustness, scalable object recognition, and vision foundation models, this book is an excellent academic resource for graduate and doctoral students, AI engineers, computer vision practitioners, data scientists, software developers, system architects, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798260001363
Comprar nuevo
EUR 275,88
Gastos de envío gratis
Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
Cantidad disponible: 1 disponibles
Imagen de archivo
Advances in Vision Foundation Models, Recognition, and Practical Systems
Librería: California Books, Miami, FL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: I-9798260001363
Comprar nuevo
EUR 278,51
Envío por EUR 2,69
Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Advances in Vision Foundation Models, Recognition, and Practical Systems (Hardcover)
Impresión bajo demandaLibrería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: new. Hardcover. Computer vision has undergone a profound transformation over the past decade, initially driven by deep convolutional neural networks and more recently by the emergence of large-scale Vision Foundation Models (VFMs). Inspired by the success of foundation models in natural language processing, approaches such as Vision Transformers (ViTs), multimodal models, and self-supervised architectures have redefined how visual understanding systems are designed, trained, and deployed. Pre-trained on massive datasets and adaptable to a wide range of downstream tasks, these models are reshaping both research and industry. From image classification and object detection to multimodal reasoning, medical imaging, autonomous systems, and intelligent surveillance, foundation-based vision systems are enabling scalable, transferable, and data-efficient solutions. Advances in Vision Foundation Models, Recognition, and Practical Systems presents a comprehensive and up-to-date exploration of developments in vision foundation models, recognition techniques, and real-world system deployment. By bridging theoretical foundations, architectural innovations, training paradigms, and practical applications, this book balances cutting-edge research insights with implementation-oriented guidance, making it both academically rigorous and highly relevant to industry. Covering topics such as adversarial robustness, scalable object recognition, and vision foundation models, this book is an excellent academic resource for graduate and doctoral students, AI engineers, computer vision practitioners, data scientists, software developers, system architects, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798260001363
Comprar nuevo
EUR 244,96
Envío por EUR 44,22
Se envía de Reino Unido a Estados Unidos de America
Se envía de Reino Unido a Estados Unidos de America
Cantidad disponible: 1 disponibles
Imagen de archivo
Advances in Vision Foundation Models, Recognition, and Practical Systems (Hardcover)
Impresión bajo demandaLibrería: AussieBookSeller, Truganina, VIC, Australia
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: new. Hardcover. Computer vision has undergone a profound transformation over the past decade, initially driven by deep convolutional neural networks and more recently by the emergence of large-scale Vision Foundation Models (VFMs). Inspired by the success of foundation models in natural language processing, approaches such as Vision Transformers (ViTs), multimodal models, and self-supervised architectures have redefined how visual understanding systems are designed, trained, and deployed. Pre-trained on massive datasets and adaptable to a wide range of downstream tasks, these models are reshaping both research and industry. From image classification and object detection to multimodal reasoning, medical imaging, autonomous systems, and intelligent surveillance, foundation-based vision systems are enabling scalable, transferable, and data-efficient solutions. Advances in Vision Foundation Models, Recognition, and Practical Systems presents a comprehensive and up-to-date exploration of developments in vision foundation models, recognition techniques, and real-world system deployment. By bridging theoretical foundations, architectural innovations, training paradigms, and practical applications, this book balances cutting-edge research insights with implementation-oriented guidance, making it both academically rigorous and highly relevant to industry. Covering topics such as adversarial robustness, scalable object recognition, and vision foundation models, this book is an excellent academic resource for graduate and doctoral students, AI engineers, computer vision practitioners, data scientists, software developers, system architects, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9798260001363
Comprar nuevo
EUR 308,06
Envío por EUR 33,13
Se envía de Australia a Estados Unidos de America
Se envía de Australia a Estados Unidos de America
Cantidad disponible: 1 disponibles
Imagen de archivo
Advances in Vision Foundation Models, Recognition, and Practical Systems
Impresión bajo demandaLibrería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Computer vision has undergone a profound transformation over the past decade, initially driven by deep convolutional neural networks and more recently by the emergence of large-scale Vision Foundation Models (VFMs). Inspired by the success of foundation models in natural language processing, approaches such as Vision Transformers (ViTs), multimodal models, and self-supervised architectures have redefined how visual understanding systems are designed, trained, and deployed. Pre-trained on massive datasets and adaptable to a wide range of downstream tasks, these models are reshaping both research and industry. From image classification and object detection to multimodal reasoning, medical imaging, autonomous systems, and intelligent surveillance, foundation-based vision systems are enabling scalable, transferable, and data-efficient solutions. Advances in Vision Foundation Models, Recognition, and Practical Systems presents a comprehensive and up-to-date exploration of developments in vision foundation models, recognition techniques, and real-world system deployment. By bridging theoretical foundations, architectural innovations, training paradigms, and practical applications, this book balances cutting-edge research insights with implementation-oriented guidance, making it both academically rigorous and highly relevant to industry. Covering topics such as adversarial robustness, scalable object recognition, and vision foundation models, this book is an excellent academic resource for graduate and doctoral students, AI engineers, computer vision practitioners, data scientists, software developers, system architects, and more. Nº de ref. del artículo: 9798260001363
Comprar nuevo
EUR 332,29
Envío por EUR 35,00
Se envía de Alemania a Estados Unidos de America
Se envía de Alemania a Estados Unidos de America
Cantidad disponible: 2 disponibles