Less-supervised Segmentation with CNNs: Scenarios, Models and Optimization reviews recent progress in deep learning for image segmentation under scenarios with limited supervision, with a focus on medical imaging. The book presents main app...Loe edasi...
This introduces artificial neural network-based Lagrange optimization techniques for structural design in prestressed concrete based on Eurocode 2 and composite structures based on American Institute of Steel Construction and American Concrete Insti...Loe edasi...
Neural networks are at the heart of AI—so ensure you’re on the cutting edge with this guide! For true beginners, get a crash course in Python and the mathematical concepts you’ll need to understand and create neural networks. Or jump right into pr...Loe edasi...
Deep learning has achieved impressive results in image classification, computer vision, and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resou...Loe edasi...
This book illustrates recent advances in Neural Artificial Intelligent Theories and Applications discussed by selected papers presented at 30th edition of the International Workshops on Neural Network (WIRN 2023). The book discusses novel technolo...Loe edasi...
A hands-on guide to powerful graph-based deep learning models! Learn how to build cutting-edge graph neural networks for recommendation engines, molecular modeling, and more.Graph Neural Networks in Action teaches you to create...Loe edasi...
(Ilmumisaeg: 01-May-2025, Hardback, Kirjastus: Springer International Publishing AG, ISBN-13: 9783031872815)
This book explores the stability analysis of neural networks and evolving intelligent systems, focusing on their ability to adapt to changing environments. It differentiates between neural networks, which have a static structure and...Loe edasi...
Turchetti (Universita Politecnica delle Marche) investigates the properties of neural networks as sources of random functions, and whether approximating properties similar to those valid for deterministic functions hold for random functions. After in...Loe edasi...
Neural approaches have traditionally excelled at perceptual tasks like pattern recognition, whereas symbolic frameworks have offered powerful methods for knowledge representation, logical inference, and interpretability, but the current AI landscape...Loe edasi...
If only it were possible to develop automated and trainable neural systems that could justify their behavior in a way that could be interpreted by humans like a symbolic system. The field of Neurosymbolic AI aims to combine two disparate approaches t...Loe edasi...
(Ilmumisaeg: 24-Apr-2025, Hardback, Kirjastus: Springer International Publishing AG, ISBN-13: 9783031830884)
The second edition of Neuromorphic Computing Principles and Organization delves deeply into neuromorphic computing, focusing on designing fault-tolerant, scalable hardware for spiking neural networks. Each chapter includes exercis...Loe edasi...
This book provides a direct method based on system solutions to address the problems related to the analysis and control of delayed neural networks. The method proposed in this book is important for the following reasons: It does not involve the c...Loe edasi...
This two volume set provides the complete proceedings of the 1990 International Joint Conference on Neural Networks held in Washington, D.C. Complete with subject, author, and title indices, it provides an invaluable reference to the current state-of...Loe edasi...
This book presents the proceedings of the NeuroIS Retreat 2024, June 9 - 11, Vienna, Austria, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findi...Loe edasi...
