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

The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024.
The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.

Anchor STARK: Query Design for Transformer-Based Target Tracking.- DACG-Net: A Dual Attention and Classifier Guided Network for Low-Light Image Enhancement.- Improved Aggregated Contextual Transformations Based on U-Net for Image Inpainting.- Mitigating Vanishing Activations in Deep CapsNets Using Channel Pruning.- A Novel Data Synthesis Method by Integration of Diffusion Model and GAN for Object Detection Task.- MOSSE-YOLOv8: A Two-Stage Approach for Small-Target Arc Detection in High-Speed Railways.- SAM-FL:Enhanced Generalizable Medical Image Segmentation via Sharpness-Aware Minimization and Focal Loss.- CP2PNet: A General End-to-End Framework for Plant Organs Counting and Phenological Stage Prediction.- Hierarchical Prompt-Enhanced Image Generation Using Hyperbolic Space.- Efficient Conditional Diffusion Model for Accurate Pedestrian
Trajectory Prediction.- MonoViM: Enhancing Self-supervised Monocular Depth Estimation via Mamba.- An End-to-End rPPG-Based Face Anti-Spoofing Network with Deception Enhancement Module.- Region-Aware Instruction-Guided Image Editing with Attention-Weighted Feature Fusion.- Multi-view Self-supervised 3D Human Pose and Shape Estimation on SMPL.- WT-based Feature Enhancement Network for Camouflaged Object Detection.- Multi-Headed Graph-based Attention aided U-Net Model for Nuclei Segmentation.- Research and Implementation of Fine-Grained Bird Image Classification.- LSC-YOLO: Small Target Defects Detection Model for Wind Turbine Blade based on YOLOv9.- SAU: A Dual-Branch Network to Enhance Long-Tailed Recognition via Generative Models.- Leveraging local similarity for token merging in Vision Transformers.- Semi-Supervised Domain Adaptation for All Weather Point Cloud Semantic Segmentation.- Federated Learning for Blind Image Super-Resolution.- Towards Better Text-to-Image Generation Alignment via Attention Modulation.- CLOFAI: A Dataset of Real And Fake Image Classification Tasks for Continual Learning.- AMSA-UNet: An Asymmetric Multiple Scales U-net Based on Self-attention for Deblurring.- MT-Net: A Dual-Encoder Multiscale Medical Segmentation Model.- ENHANCING ADVERSARIAL ROBUSTNESS OF DIFFUSION DENOISED SMOOTHING VIA IMAGE SUPER-RESOLUTION.- A simultaneous hierarchical count data clustering and feature selection based on Multinomial Nested Dirichlet Mixture using the Minorization-Maximization framework.