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E-raamat: Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 20-23, 2023, Proceedings, Part V

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The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. 

The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. 

Text to Image Generation with Conformer-GAN.- MGFNet: A
Multi-Granularity Feature Fusion and Mining Network for Visible-Infrared
Person Re-Identification.- Isomorphic Dual-Branch Network for Non-homogeneous
Image Dehazing and Super-Resolution.- Hi-Stega : A Hierarchical Linguistic
Steganography Framework Combining Retrieval and Generation.- Effi-Seg:
Rethinking EfficientNet Architecture for Real-time Semantic
Segmentation.- Quantum Autoencoder Frameworks for Network Anomaly
Detection.- Spatially-Aware Human-Object Interaction Detection with
Cross-Modal Enhancement.-  Intelligent trajectory tracking control of
unmanned parafoil system based on SAC optimized LADRC.- CATS:
Connection-aware and Interaction-based Text Steganalysis in Social
Networks.- Syntax Tree Constrained Graph Network for Visual Question
Answering.- CKR-Calibrator: Convolution Kernel Robustness Evaluation and
Calibration.- SGLP-Net: Sparse Graph Label Propagation Network for
Weakly-Supervised Temporal Action Localization.- VFIQ: A Novel Model of
ViT-FSIMc Hybrid Siamese Network for Image Quality Assessment.- Spiking
Reinforcement Learning for Weakly-supervised Anomaly
Detection.- Resource-aware DNN Partitioning for Privacy-sensitive Edge-Cloud
Systems.- A frequency reconfigurable multi-mode printed antenna.-  Multi-view
Contrastive learning for Knowledge-aware Recommendation.- PYGC: a PinYin
Language Model Guided Correction Model for Chinese Spell Checking.- Empirical
Analysis of Multi-label Classification on GitterCom using BERT.- A
lightweight safety helmet detection network based on bidirectional connection
module and Polarized Self-Attention.- Direct Inter-Intra View Association for
Light Field Super-Resolution.- Responsive CPG-Based Locomotion Control for
Quadruped Robots.- Vessel Behavior Anomaly Detection using Graph Attention
Network.- TASFormer: Task-aware Image Segmentation
Transformer.-  Unsupervised Joint-Semantics Autoencoder Hashing for
Multimedia Retrieval.- TKGR-RHETNEA New Temporal Knowledge Graph Reasoning
Model via Jointly Modeling Relevant Historical Event and Temporal
Neighborhood Event Context.- High-Resolution Self-Attention with Fair Loss
for Point Cloud Segmentation.- Transformer-based Video Deinterlacing
Method.- SCME: A Self-Contrastive Method for Data-free and Query-Limited
Model Extraction Attack.- CSEC: A Chinese Semantic Error Correction Dataset
for Written Correction.- Contrastive Kernel Subspace Clustering.- UATR: An
Uncertainty Aware Two-stage Refinement Model for Targeted Sentiment
Analysis.- AttIN: Paying More Attention to Neighborhood Information for
Entity Typing in Knowledge Graphs.- Text-based Person Re-ID by Saliency Mask
and Dynamic Label Smoothing.- Robust Multi-view Spectral Clustering with
Auto-encoder for Preserving Information.-  Learnable Color Image
Zero-Watermarking Based on Feature Comparison.-  P-IoU: Accurate Motion
Prediction based Data Association for Multi-Object Tracking.- WCA-VFnet:a
dedicated complex forest smoke fire detector.- Label Selection Algorithm
Based on Ant Colony Optimization and Reinforcement Learning for Multi-label
Classification.- Reversible Data Hiding Based on Adaptive Embedding with
Local Complexity.- Generalized Category Discovery with Clustering Assignment
Consistency.- CInvISP: Conditional Invertible Image Signal Processing
Pipeline.- Ignored Details in Eyes: Exposing GAN-generated Faces by
Sclera.- A Developer Recommendation Method Based on Disentangled.- Graph
Convolutional Network.- Novel Method for Radar Echo Target Detection.