Advances in Neural Networks – ISNN 2025
Springer Verlag, Singapore
978-981-95-1232-4 (ISBN)
The 52 full papers were carefully reviewed and selected from 60 submission.
This volume constitutes the refereed proceedings of the 19th International Symposium on Neural Networks, ISNN 2025, held in Zhangye, China, during August 22 24, 2025.
The 52 full papers were carefully reviewed and selected from 60 submission. They were organized in topical sections as follows: Design, Modeling and Application of AI Algorithms; Signal, Image, and Video Processing; Modeling, Analysis, and Implementation of Neural Networks; Control Systems, Robotics, and Autonomous Driving; Machine Learning Methods and Applications.
.- Design, Modeling and Application of AI Algorithms.
.- Hybrid Architecture Accelerator Co-design for DNN on FPGA and ASIC.
.- Modeling Competitive Behavior in Weight-Unbalanced Social Networks.
.- DeeP-Mod: Deep Dynamic Programming based Environment Modelling using Feature Extraction.
.- Muography Inversion Based on First-Order Optimization Algorithm.
.- Regression-based Index Tracking versus Clustering-based Index Tracking: An Empirical Study.
.- Adversarial Imitation Learning Based on Weighted Wasserstein Distance.
.- Robust and Efficient Early Exit for Large Language Models: Mitigating KV Cache Loss and Enhancing Exit Stability.
.- CDEDI: A Conditional Diffusion Based Model for Environmental Data imputation.
.- Joint Forecasting of Stock Price Change Rate Based on Pretrained Models Using Text and Temporal Data.
.- Multimodal Deep Learning for Retinal Disease Diagnosis.
| Erscheinungsdatum | 23.08.2025 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | 193 Illustrations, color; 22 Illustrations, black and white |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Mathematik / Informatik ► Mathematik ► Analysis | |
| Schlagworte | Adversarial Learning • Autonomous Driving • Deep learning • Distributed Systems • Fault Diagnosis • memristor • Neural networks • Neurodynamics • Optimization • transfer learning |
| ISBN-10 | 981-95-1232-8 / 9819512328 |
| ISBN-13 | 978-981-95-1232-4 / 9789819512324 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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