Buch, Englisch, 686 Seiten, Format (B × H): 155 mm x 235 mm
7th International Conference, NCAA 2026, Osaka, Japan, July 9-12, 2026, Proceedings
Buch, Englisch, 686 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Communications in Computer and Information Science
ISBN: 978-981-9267-02-6
Verlag: Springer Nature Singapore
This volume constitutes the refereed proceedings of the 7th International Conference on Neural Computing for Advanced Applications, NCAA 2026, held in Osaka, Japan during July 9–12, 2026.
The 45 full papers presented in these proceedings were carefully reviewed and selected from 99 submissions.
The papers are organized in the following topical sections: Computational intelligence, nature-inspired optimizers, and their engineering applications; Deep learning-driven pattern recognition, computer vision and its industrial applications; Machine learning and deep learning for data mining and data-driven applications; Multimodal Deep Learning for Represeantation, Fusion and Applications; Natural language processing, knowledge graphs, recommender systems, and their applications and Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
- Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
- Mathematik | Informatik EDV | Informatik Technische Informatik
Weitere Infos & Material
.- Computational intelligence, nature-inspired optimizers, and their engineering applications.
.- MPC-Guided Online Gain Calibration of PID Controllers in Uncertain Environments.
.- A Retrieval- and Ontology-Augmented Generation Framework for Explainable Human-Centric Decision Support in Industry 5.0.
.- Domain-Generalized Remaining Useful Life Prediction via Complementary Multi-Strategy Learning.
.- Dendritic Neural Integration with Homeostatic Plasticity for Few-Shot Molecular Property Prediction.
.- STF-Polyp: Spatio-Temporal Fusion for Polyp Detection and Tracking in Endoscopic Videos.
.- From Programmable Logic Controller (PLC) Simulation to Explainable Decision Support: A Practical Industry 5.0 Demonstration Using ThingsBoard and Large Language Models (LLMs).
.- The Implementation of Metrology Comparisons by Technical Institutions.
.- Deep learning-driven pattern recognition, computer vision and its industrial applications.
.- Physics-Guided Safety Gating: Balancing Structure Preservation and Raindrop Removal.
.- HighPhytoSparseNet: A Lightweight Multi-Head Object Detection Model for Edge-Based Agricultural Applications.
.- YOLO-Based Vehicle Detection for Night-time Highway Surveillance.
.- Adaptive Detector Scheduling for Multi-Object Tracking in Edge Video Analytics Systems.
.- Disentangling Texture Latent Space for Unsupervised Garment Generation via PCA Decomposition.
.- Boundary-Enhanced Side Adapter Network for Autonomous Driving.
.- A Hybrid Network for Dual-XRT Ore Segmentation in Complex Adhesion Scenarios.
.- Machine learning and deep learning for data mining and data-driven applications.
.- Hierarchical Evidential Multi-Target Learning with Progressive Confidence for Diabetes Prediction: A large-scale study.
.- Direct Multi-horizon Prediction of Multi-point Landslide Displacement via Point-level Spatiotemporal Feature Learning.
.- GL-Guide: A Dynamic Grouping Multi-Agent Reinforcement Learning Framework for Traffic Guidance.
.- Spectral Clustering for Discrete Distributions.
.- Garment-Scene Model: Decoupled Multi-Modal Diffusion for Virtual Try-On and Contextual Generation.
.- An integrated decision-making method based on neighborhood rough sets and the VIKOR method.
.- A Robot Task Planning Method based on Large Language Models with Self-Feedback Constraint Optimization.
.- Research on Firm Responses and Efficiency Improvement under the Dual Economic Effects of Technical Barriers to Trade: An Empirical Study Based on LASSO Variable Selection and DML Causal Inference.
.- A Generalized Category Discovery Method with Two-stage Similarity Discriminant for Continuous Data Stream.
.- Bayesian SNR-Driven Structured Pruning for Convolutional Neural Networks.
.- Enhanced Grey Wolf Optimizer with PSO Elite Injection for Build-up Rate Maximization.
.- Multimodal Deep Learning for Represeantation, Fusion and Applications.
.- Fuzzy Control Adaptive Chain-of-Thought Reasoning for Multimodal Target Sentiment Classification.
.- LM2A: Lyrics and Motion to Audio Generation with Multi-Conditional Diffusion.
.- Log-Domain Dendritic Neuron Model Backends for Multimodal Molecular Property Prediction.
.- Robust Supervised Discriminant Hashing (RSDH) for Image Retrieval.
.- Enhancing Bearing Fault Diagnosis under Distribution Shift via LLM-Based Multi-View Multimodal Retrieval Augmented Reasoning.
.- Natural language processing, knowledge graphs, recommender systems, and their applications.
.- Weighted Bidirectional LSTM with Dynamic Attention for Logographic News Text Classification.
.- Contextual Rescoring of Top-k Character Candidates for Kuzushiji OCR.
.- NLG-Gen: Natural Language-Guided Generation of Long-Tail Critical Scenarios for Autonomous Driving.
.- Large Language Model-Driven Distributional Disease Similarity Graph Construction.
.- SCRROM: Subgraph Contrastive Learning with Retrieval-Based Reasoning for Ontology Matching.
.- Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications.
.- Static vs Trainable Routers in Mixture-of-Experts for GNN-Based Key Node Identification under Distributional Shifts.
.- Sequential Transformer-Based Variational Autoencoder for EEG Data Augmentation in Emotion Recognition.
.- Informed-PGAM-RRT*: Efficient Path Planning in Constrained Environments via Guided Sampling and Adaptive Metrics.
.- Predictive Recurrent Graph Attention Reinforcement Learning for Dynamic Target Scheduling in PTZ-Based UAV Monitoring.
.- Intent-Enhanced Reinforcement Learning for Beyond-Visual-Range Air Combat.
.- Generalizable Neural Observer Design with Learned Riemannian Metrics for State Estimation.
.- Curriculum Reinforcement Learning for Launch Vehicle Orbital Flight Phase Trajectory Optimization under Thrust Faults.
.- Difference-of-Convex Optimization for Non-Euclidean Contraction Design of Hopfield Neural Networks.
.- Safe Landing of Rotary Wing Aircraft with Tail Rotor Jamming Based on Deep Reinforcement Learning.
.- Autorotation Landing Control of Rotorcraft Using Twin Delayed Deep Deterministic Policy Gradient With Temporal Attention.
