Neural Information Processing 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2–6, 2024, Proceedings, Part XI

The eleven-volume set LNCS 15286-15295 constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024.

The 318 regular papers presented in the proceedings set were carefully reviewed and selected from 1301 submissions. They focus on four main areas, namely: theory and algorithms; cognitive neurosciences; human-centered computing; and applications.

Human activity recognition model capable of handling various input waveforms.- Enhance Radar Point Cloud with 2D Diffusion.- LBRFL: Lightweight Privacy-Preserving Federated Learning with Byzantine-Robustness.- Izhikevich Neurons in NeuCube for Longitudinal Data Classification.- Calming the mind: Spiking Neural Networks Reveal How Havening Touch to Reduce Persistent Distress Attenuates Left Temporal Electroencephalographic Connectivity.- SCA-LSTM: A Deep Learning Approach to Golf Swing Analysis and Performance Enhancement.- Unsupervised Document Image Tampering Localization via Anomaly Detection.- 3VNet: Topological-structure driven Triple-V Network for Retinal Vessel Segmentation.- Identification of Proton Exchange Membrane Fuel Cell Parameters Using a Parameterless Swarm Intelligent Algorithm.- Spatio-Temporal Graph Neural Networks for Infant Language Acquisition Prediction.- AUV Efficient Navigation Relying on Adaptive Proximal Policy Optimization.- MedSiML: A Multilingual Approach for Simplifying Medical Texts.- A Study on Time-Resilient Features for Detecting TLS Encrypted Malware Traffic.- Enhancing Semantic Segmentation in Open Compound Domain Adaptation through Mixed Image and Epistemic Uncertainty.- What should insect brains forget?.- Agent Clustering and Information Sharing Underlying MADRQN for Traffc Light Cooperative Control.- A Hybrid Contextual Deep Learning Model to Predict Renewable Energy Generation.- Knowledge Tracing Method Based on Enhanced Global and Local Knowledge State Representation.- Tensor Mutual Information: A Similarity Measurement for High-Dimensional Data.- Enforcing Specific Behaviours via Constrained DRL and Scenario-Based Programming.- Explainable AI in Feature Selection: Improving Classification Performance on Imbalanced Datasets.- Enhancing Industrial Energy Efficiency with Predictive Analytics and Fuzzy Logic: A Case Study of Renewable Energy Management in the Meat Processing Industry.- A Dual-Branch Riemannian Learning Network for EEG Speech Imagery Decoding.- ROSAL: Semi-supervised Active Learning with Representation Aggregation and Outlier for Endoscopy Image Classification.- Adaptive Population-Based Incremental Learning for Feature Selection in Leukemia Gene Expression Data.