Full Description
The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26-29, 2023.
The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.
Contents
Advancing Brain Tumor Detection with Multiple Instance Learning on Magnetic Resonance Spectroscopy Data.- An Echo State Network-Based Method for Identity Recognition with Continuous Blood Pressure Data.- Analysis and Interpretation of ECG Time series through Convolutional Neural Networks in Brugada Syndrome Diagnosis.- Analysis of Augmentations in Contrastive Learning for Parkinson's Disease Diagnosis.- BF-Net: A Fine-Grained Network for Identify Bacterial and Fungal Keratitis.- Bilateral Mammogram Mass Detection Based On Window Cross Attention.- Boundary Attentive Spatial Multi-Scale Network For Cardiac MRI Image Segmentation.- Clinical pixel feature recalibration module for ophthalmic image classification.- CopiFilter: An Auxiliary Module Adapts Pre-trained Transformers for Medical Dialogue Summarization.- IESBU-Net: A lightweight skin lesion segmentation UNet with inner-module extension and skip-connection bridge.- Molecular Substructure-based Double-Central Drug-Drug Interaction prediction.- Prediction of cancer drug sensitivity based on GBDT-RF algorithm.- Risk stratification of malignant melanoma using neural networks.- Symmetry-Aware Siamese Network: Exploiting Pathological Asymmetry for Chest X-Ray Analysis.- The Optimization and Parallelization of Two-Dimensional Zigzag Scanning on the Matrix.- Tooth segmentation from Cone-Beam CT Images through boundary refinement.- Transformer Based Prototype Learning for Weakly-Supervised Histopathology Tissue Semantic Segmentation.- A Balanced Relation Prediction Framework for Scene Graph Generation.- A Graph Convolutional Siamese Network for Assessment and Recognition Physical Rehabilitation Exercises.- A Graph Neural Network-based Smart Contract Vulnerability Detection Method With Artificial Rule.- Adaptive Randomized Graph Neural Network based on Markov Diffusion Kernel.- Adaptive Weighted Multi-View Evidential Clustering.- An untrained neural model for fast and accurate graph classification.- BGEK: External Knowledge-enhanced Graph Convolutional Networks for Rumor Detection in Online Social Networks.- BIG-FG: A Bi-directional Interaction Graph Framework with Filter Gate Mechanism for Chinese Spoken Language Understanding.- Co-RGCN: A Bi-path GCN-based Co-Regression model for Multi-intent Detection and Slot Filling.- DNFS: a Digraph Neural Network with the First-order and the Second-order Similarity.- Efficient Question Answering Based on Language Models and Knowledge Graphs.- Event association analysis using graph rules.- Fake Review Detection via Heterogeneous Graph Attention Network.- GatedGCN with GraphSage to Solve Traveling Salesman Problem.- GNN Graph Classification Method to Discover Climate Change Patterns.- GNN-MRC: Machine Reading Comprehension based on GNN Augmentation.- Graph Convolutional Network Semantic Enhancement Hashing for Self-supervised Cross-Modal Retrieval.- Heterogeneous Graph Neural Network Knowledge Graph Completion Model Based on Improved Attention Mechanism.- Hierarchical Diachronic Embedding of Knowledge Graph combined with Fragmentary Information Filtering.- K-DLM: A Domain-Adaptive Language Model Pre-Training Framework with Knowledge Graph.- Label Enhanced Graph Attention Network for Truth Inference.- LogE-Net: Logic evolution network for temporal knowledge graph forecasting.- LTNI-FGML: Federated Graph Machine Learning on Long-Tailed and Non-IID Data via Logit Calibration.- Multi-Granularity Contrastive Learning for Graph with Hierarchical Pooling.- Multimodal Cross-Attention Graph Network for Desire Detection.- Negative Edge Prediction for Attributed Graph Clustering.- One-Class Intrusion Detection with Dynamic Graphs.- Sequence-based Modeling for Temporal Knowledge Graph Link Prediction.- Structure-Enhanced Graph Neural ODE Network for Temporal Link Prediction.- Supervised Attention Using Homophily in Graph Neural Networks.- Target-oriented Sentiment Classification with Sequential Cross-modal Semantic Graph.
