Recent Advances in Artificial Neural Networks: Case Studies and Applications - Couverture rigide

9783032134967: Recent Advances in Artificial Neural Networks: Case Studies and Applications

Couverture rigide

ISBN 10 : 303213496X ISBN 13 : 9783032134967

Editeur : Springer Nature Switzerland AG, 2026

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This book compiles research on the practical implementation of deep learning models and hybrid intelligent systems to tackle diverse and impactful challenges. Artificial Neural Networks (ANNs) and deep learning have profoundly transformed how real-world problems are addressed, enabling intelligent and adaptive solutions across various domains, including agriculture, healthcare, surveillance, natural language processing, multimodal learning, and environmental monitoring. Each chapter presents a specific use case, employing advanced techniques such as LSTM networks, hybrid CNN–BiLSTM architectures, siamese networks, attention mechanisms, YOLO-based object detection models, transformer architectures, and fuzzy inference systems. The collection is distinguished by its methodological rigor and the breadth of its application areas. To ensure a coherent and structured reading experience, this book is organized into three thematic sections: (1) Forecasting and Predictive Modeling, (2) Computer Vision and Multimodal Recognition, and (3) Innovations in Deep Learning Architectures and Applications. This book is a valuable resource for researchers, professionals, graduate students, and practitioners interested in the current landscape and future directions of deep learning. Readers from disciplines such as computer science, engineering, data science, health informatics, and applied artificial intelligence find inspiration and practical guidance for advancing their work in this book.

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�diteur: Springer Nature Switzerland AG
Date d'�dition: 2026
Langue: anglais
ISBN 10: 303213496X
ISBN 13: 9783032134967
Reliure: Reli�
Nombre de pages: 590
�diteur: Rivera Gilberto, Pedrycz Witold, Labella �lvaro, Florencia Rogelio
Coordonn�es du fabricant: Springer Nature Customer Service Center GmbH
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Recent Advances in Artificial Neural Networks (Hardcover)

Gilberto Rivera

Edit� par Springer Nature Switzerland AG, Cham, 2026

ISBN 10 : 303213496X ISBN 13 : 9783032134967

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Hardcover. Etat : new. Hardcover. This book compiles research on the practical implementation of deep learning models and hybrid intelligent systems to tackle diverse and impactful challenges. Artificial Neural Networks (ANNs) and deep learning have profoundly transformed how real-world problems are addressed, enabling intelligent and adaptive solutions across various domains, including agriculture, healthcare, surveillance, natural language processing, multimodal learning, and environmental monitoring. Each chapter presents a specific use case, employing advanced techniques such as LSTM networks, hybrid CNNBiLSTM architectures, siamese networks, attention mechanisms, YOLO-based object detection models, transformer architectures, and fuzzy inference systems. The collection is distinguished by its methodological rigor and the breadth of its application areas. To ensure a coherent and structured reading experience, this book is organized into three thematic sections: (1) Forecasting and Predictive Modeling, (2) Computer Vision and Multimodal Recognition, and (3) Innovations in Deep Learning Architectures and Applications. This book is a valuable resource for researchers, professionals, graduate students, and practitioners interested in the current landscape and future directions of deep learning. Readers from disciplines such as computer science, engineering, data science, health informatics, and applied artificial intelligence find inspiration and practical guidance for advancing their work in this book. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9783032134967

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Recent Advances in Artificial Neural Network

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Recent Advances in Artificial Neural Networks

Gilberto Rivera

Edit� par Springer Nature Switzerland AG Jul 2026, 2026

ISBN 10 : 303213496X ISBN 13 : 9783032134967

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book compiles research on the practical implementation of deep learning models and hybrid intelligent systems to tackle diverse and impactful challenges. Artificial Neural Networks (ANNs) and deep learning have profoundly transformed how real-world problems are addressed, enabling intelligent and adaptive solutions across various domains, including agriculture, healthcare, surveillance, natural language processing, multimodal learning, and environmental monitoring. Each chapter presents a specific use case, employing advanced techniques such as LSTM networks, hybrid CNN BiLSTM architectures, siamese networks, attention mechanisms, YOLO-based object detection models, transformer architectures, and fuzzy inference systems. The collection is distinguished by its methodological rigor and the breadth of its application areas. To ensure a coherent and structured reading experience, this book is organized into three thematic sections: (1) Forecasting and Predictive Modeling, (2) Computer Vision and Multimodal Recognition, and (3) Innovations in Deep Learning Architectures and Applications. This book is a valuable resource for researchers, professionals, graduate students, and practitioners interested in the current landscape and future directions of deep learning. Readers from disciplines such as computer science, engineering, data science, health informatics, and applied artificial intelligence find inspiration and practical guidance for advancing their work in this book. 573 pp. Englisch. N� de r�f. du vendeur 9783032134967

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Recent Advances in Artificial Neural Networks: Case Studies and Applications (Intelligent Systems Reference Library, 283)

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Recent Advances in Artificial Neural Networks | Case Studies and Applications

Gilberto Rivera (u. a.)

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ISBN 10 : 303213496X ISBN 13 : 9783032134967

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Recent Advances in Artificial Neural Networks

Gilberto Rivera

Edit� par Palgrave Macmillan Aug 2026, 2026

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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book compiles research on the practical implementation of deep learning models and hybrid intelligent systems to tackle diverse and impactful challenges. Artificial Neural Networks (ANNs) and deep learning have profoundly transformed how real-world problems are addressed, enabling intelligent and adaptive solutions across various domains, including agriculture, healthcare, surveillance, natural language processing, multimodal learning, and environmental monitoring. Each chapter presents a specific use case, employing advanced techniques such as LSTM networks, hybrid CNNBiLSTM architectures, siamese networks, attention mechanisms, YOLO-based object detection models, transformer architectures, and fuzzy inference systems. The collection is distinguished by its methodological rigor and the breadth of its application areas. To ensure a coherent and structured reading experience, this book is organized into three thematic sections: (1) Forecasting and Predictive Modeling, (2) Computer Vision and Multimodal Recognition, and (3) Innovations in Deep Learning Architectures and Applications. This book is a valuable resource for researchers, professionals, graduate students, and practitioners interested in the current landscape and future directions of deep learning. Readers from disciplines such as computer science, engineering, data science, health informatics, and applied artificial intelligence find inspiration and practical guidance for advancing their work in this book.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 592 pp. Englisch. N� de r�f. du vendeur 9783032134967

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Recent Advances in Artificial Neural Networks (Hardcover)

Gilberto Rivera

Edit� par Springer Nature Switzerland AG, Cham, 2026

ISBN 10 : 303213496X ISBN 13 : 9783032134967

Neuf Couverture rigide

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Hardcover. Etat : new. Hardcover. This book compiles research on the practical implementation of deep learning models and hybrid intelligent systems to tackle diverse and impactful challenges. Artificial Neural Networks (ANNs) and deep learning have profoundly transformed how real-world problems are addressed, enabling intelligent and adaptive solutions across various domains, including agriculture, healthcare, surveillance, natural language processing, multimodal learning, and environmental monitoring. Each chapter presents a specific use case, employing advanced techniques such as LSTM networks, hybrid CNNBiLSTM architectures, siamese networks, attention mechanisms, YOLO-based object detection models, transformer architectures, and fuzzy inference systems. The collection is distinguished by its methodological rigor and the breadth of its application areas. To ensure a coherent and structured reading experience, this book is organized into three thematic sections: (1) Forecasting and Predictive Modeling, (2) Computer Vision and Multimodal Recognition, and (3) Innovations in Deep Learning Architectures and Applications. This book is a valuable resource for researchers, professionals, graduate students, and practitioners interested in the current landscape and future directions of deep learning. Readers from disciplines such as computer science, engineering, data science, health informatics, and applied artificial intelligence find inspiration and practical guidance for advancing their work in this book. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9783032134967

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Recent Advances in Artificial Neural Networks : Case Studies and Applications

Gilberto Rivera

Edit� par Springer, Berlin, Springer, 2026

ISBN 10 : 303213496X ISBN 13 : 9783032134967

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book compiles research on the practical implementation of deep learning models and hybrid intelligent systems to tackle diverse and impactful challenges. Artificial Neural Networks (ANNs) and deep learning have profoundly transformed how real-world problems are addressed, enabling intelligent and adaptive solutions across various domains, including agriculture, healthcare, surveillance, natural language processing, multimodal learning, and environmental monitoring. Each chapter presents a specific use case, employing advanced techniques such as LSTM networks, hybrid CNN BiLSTM architectures, siamese networks, attention mechanisms, YOLO-based object detection models, transformer architectures, and fuzzy inference systems. The collection is distinguished by its methodological rigor and the breadth of its application areas. To ensure a coherent and structured reading experience, this book is organized into three thematic sections: (1) Forecasting and Predictive Modeling, (2) Computer Vision and Multimodal Recognition, and (3) Innovations in Deep Learning Architectures and Applications. This book is a valuable resource for researchers, professionals, graduate students, and practitioners interested in the current landscape and future directions of deep learning. Readers from disciplines such as computer science, engineering, data science, health informatics, and applied artificial intelligence find inspiration and practical guidance for advancing their work in this book. N� de r�f. du vendeur 9783032134967

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