Jin / Wang Advances in Neural Networks – ISNN 2025

19th International Symposium on Neural Networks, Zhangye, China, August 22–24, 2025, Proceedings
Erscheinungsjahr 2025
ISBN: 978-981-951233-1
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 597 Seiten

Reihe: Computer Science (R0)

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.

Zielgruppe

Research

Autoren/Hrsg.

Jin, Long

Wang, Lidan

Inhaltsverzeichnis

.- 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.