| 紀錄類型: |
書目-電子資源
: Monograph/item
|
| 正題名/作者: |
Advanced intelligent computing technology and applications/ edited by De-Shuang Huang ... [et al.]. |
| 其他題名: |
21st International Conference, ICIC 2025, Ningbo, China, July 26-29, 2025 : proceedings. |
| 其他題名: |
ICIC 2025 |
| 其他作者: |
Huang, De-Shuang. |
| 團體作者: |
International Conference on Intelligent Computing |
| 出版者: |
Singapore :Springer Nature Singapore : : 2025., |
| 面頁冊數: |
xxi, 537 p. :ill. (some col.), digital ;24 cm. |
| 內容註: |
Neural Networks. -- Event Data Classification using TPE-based Deep Spiking Neural Networks. -- TIINet: A Three-Stage Interactive Integration Network for RGB-D Salient Object Detection. -- Dynamic Semantic Graph Learning with Progressive Alignment for Image-Text Matching. -- MGTDGraph: Multi-granularity Graph Attention Networks for Multivariate Long-term Time Series Forecasting. -- Topology-Aware Discriminative Graph Convolutional Network for Skeleton-Based Action Recognition. -- Online Delay Learning Algorithm for Feedforward Spiking Neural Networks Based on Spike Train Kernels. -- Energy-Constrained UAV Network Topology Recovery Based on Graph Convolutional Networks. -- UBDet: An Unsupervised Breast Tumor Detection Framework with Boundary-Aware Enhancement. -- Bidirectional Interactive Prompt Fusion and Noise Filtering for Multimodal Aspect-Based Sentiment Analysis. -- AMTerrain: Research on Arbitrary-Modal Terrain Segmentation Based on Text Guidance. -- Correlation Adaptive Dynamic Graph Convolutional Networks for Traffic Flow Prediction. -- EMDC-YOLO: A Residual Multi-Scale Attention and Cross-Scale Fusion based Method for Pedestrian Detection in Crowded Scenes. -- A Novel Lightweight YOLO Method for Satellite Remote Sensing via Matrix Decomposition. -- TSMDM-Net: A Speech Emotion Recognition Model Based on Multi-Scale Time Series Dynamic Modeling. -- Research on Contrastive Learning-Based Knowledge Distillation for Deep Graph Neural Networks. -- Two-view Fusion Graph Neural Networks for Graph Classification. -- MambaForDIF: Distance-Importance Features and Long-Range Dependencies for Enhancing Aspect-Based Sentiment Analysis. -- FedCWE: Federated Cluster-based Weight Sampling and Ensemble Learning for Non-IID Data. -- ORE: an Offline Redundancy Elimination System for GNN Acceleration. -- Time Efficiency: Legendre Polynomials in Kolmogorov-Arnold Network. -- SCAUnet: Symmetric Cross-Attention U-net model for Semantic Segementation. -- Self-Attention Multiscale Mixed Propagation Network Based on Contrastive Augmentation. -- Sentiment Perception from Tokens: A Multitask Learning Framework with Entropy-Driven Fusion. -- GCLCP: Graph Contrastive Learning with Convolutional Perturbation for Recommendation. -- Agro-LLaVA-Next: A Large Multimodal Model for Plant Diseases Recognization. -- LTL-GCL:A more efficient layer-to-layer graph contrastive learning method for recommender system. -- IMVGCN : Interactive Multi-view Learning Graph Convolutional Networks for Traffic Flow Forecasting. -- An Inverse Cavity Scattering Inversion Method Based On Adaptive Neural Fuzzy Inference System. -- Entity Backdoor Attacks Against Fine-Tuned Models. -- Knowledge Graph Denoising with Dual Contrast for Recommendation. -- DDformer: Deepfake Detection with Multimodal Fusion Transformer. -- Improved Transfer Learning based on Increased Model Capacity and Weight Re-initialization for ResNet. -- BEVboost: Research on 3D Object Detection Method for Roadside Based on Multi-Feature Fusion. -- ARG-Net:Gaze Estimation Based on Adversarial Learning and Learnable Networks. -- GNN Advanced Heuristics Algorithm for Solving Multi-Depot Vehicle Problem. -- MSDBNet: A Multi-Scale and Dual-Branch Network for Cross-Domain Person Re-identification. -- Global and Local Feature Enhancement for Short Video Fake News Detection. -- SpikingRM: Efficient Scheduling Algorithm Based on Spiking Neural Network and Deep Reinforcement Learning. -- Infrared Multi-Scale Target Detection Based on Improved YOLOv11 and Spatiotemporal Features. -- Hierarchical Attention-Driven Dynamic Graph Neural Networks for Accurate Supply Chain Demand Forecasting. -- DHCBR: Evaluating the Influence of Supply Chain Complex Network Nodes Based on ResNet. -- An Efficient DNN Training Method with Progressive Pruning. -- TPKD: Teacher-Pruned Knowledge Distillation for Point Cloud-Based 3D Object Detection. -- Network Protocol Security Evaluation via LLM-enhanced Fuzzing in Extended ProFuzzBench. |
| Contained By: |
Springer Nature eBook |
| 標題: |
Computational intelligence - Congresses. - |
| 電子資源: |
https://doi.org/10.1007/978-981-95-0009-3 |
| ISBN: |
9789819500093 |