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Full Description
This book constitutes the refereed post-conference proceedings of 4th International Symposium on Intelligent Unmanned Systems and Artificial Intelligence, SIUSAI 2025, in Hangzhou, China, during August 15-17, 2025.
The 37 full papers presented in this volume were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: Perception and Scene Understanding for Intelligent Unmanned System; AI-Driven Control, Planning and Decision-Making; Predictive Modeling and Data Intelligence for Autonomous Operations.
Contents
.- Section Ⅰ: Perception and Scene Understanding for Intelligent Unmanned Systems.
.- RCSTNet: Integrating Convolutional and Transformer Features for Semantic Segmentation of Remote
Sensing Images.
.- VFBGM: Very Fast Block-wise Gradient Magnitude-based Quality Metric for Infrared Images.
.- A Tactile Perception System for Biomimetic Whisker Robots Using SNNs.
.- A Real-time Vehicle Detection and Re-ID System from the Drone Perspective.
.- Dynamic Multi-scale Class Activation Mapping (DMs-CAM) for Enhanced Explainability in Diabetic
Retinopathy Classification.
.- CA-LWNet: A Lightweight Network for Handwritten Dongba Character Recognition.
.- Video Frame Interpolation Based on Unsupervised Deep Learning.
.- A Benchmark Large-Size Industrial Combustion Image Dataset for Fire and Smoke Segmentation.
.- Automated Training Data Generation for AI Based on Perspective Transformation and Image Synthesis.
.- YOLO-DCR: Vehicle Instance Segmentation Algorithm in Complex Scenes Based on Improved YOLOv8-
seg.
.- A Review of Infrared and Visible Light Image Fusion Algorithms.
.- A Survey on Low-Light Object Detection: Architectures, Strategies, and Future Directions.
.- Cardiovascular Disease Diagnosis Method Based on AMEsim Simulation and Convolutional Neural
Networks.
.- Section Ⅱ: AI-Driven Control, Planning and Decision-Making.
.- Path Tracking Control for Autonomous Vehicles with GP-MPC Considering System Uncertainty.
.- Application of Anti-unmanned Technology in Wartime Material Support.
.- Dynamically Stabilized Q-Learning for Model-Free Optimal Tracking Control.
.- FPGA-Based Implementation of an RBF-PID Neural Network for Adaptive Parameter Tuning.
.- A Collaborative Assessment of Anti-UAV Cluster Operational Effectiveness Based on BP Neural Network
and FAHP-TOPSIS.
.- Application of Deep Reinforcement Learning in Obstacle Avoidance and Inspection Path Planning for UAVs in Complex Vegetation Environments.
.- Task Allocation and Trajectory Planning in UAV Formation Counter-swarm Missions.
.- Multi-unmanned Underwater Vehicles Cooperative Obstacle Avoidance Method Based on Artificial Potential Field Method and DQN.
.- Research on the Application of US Army Robot Birds.
.- Enhancing Unmanned Systems Autonomy Evaluation: A Scalable Framework for Adaptive Scenario-Task Integration.
.- Integrated Intelligence Evaluation for Unmanned Systems Using Dempster-Shafer Fusion.
.- Multi-sensor Fusion for LiDAR SLAM: A Survey of Development.
.- Globally Consistent Non-Rigid Map Fusion for MASt3R-SLAM.
.- Section Ⅲ: Predictive Modeling and Data Intelligence for Autonomous Operations.
.- Short Term Power Load Forecasting by AP Frequency Clustering and LSTM.
.- Fourier Decomposition Residual-Based Power Load Forecasting.
.- LSTM based Short-Term Load Forecasting via Ensemble Empirical Mode Decomposition and Graph
Clustering.
.- A DWT-LSTM Hybrid Model for Temperature Prediction in the Cement Kiln.
.- Ship Heave Motion Prediction Using an Integrated EMD and Sequential Learning Approach.
.- A Model for Off Target Distance of Supersonic Projectile with Oblique Incidence.
.- Terminal Trajectory and Impact Point Localization of Subsonic Landing Unexploded Projectiles.
.- Identifying Legal Core Elements Based on Extra-Long Network and Bidirectional Long Short-Term Memory.
.- A Method Framework for Exploratory Analysis of Open Source Combat Losses Data.
.- Municipal Solid Waste Incineration Digital Twin: Framework, Key Technologies, and Future Prospect.
.- Scalable Hybrid Framework for Domain Patent Knowledge Graph Construction Using Deep Learning and Graph Databases.
