Artificial Neural Networks and Machine Learning – ICANN 2023 -

Artificial Neural Networks and Machine Learning – ICANN 2023

32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part IX
Buch | Softcover
XXXIV, 523 Seiten
2023 | 1st ed. 2023
Springer International Publishing (Verlag)
978-3-031-44200-1 (ISBN)
87,73 inkl. MwSt

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 and 9 short 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.


MEA-TransUNet: a Multiple External Attention Network for Multi-Organ Segmentation.- Membership-Grade Based Prototype Rectification for Fine-Grained Few-Shot Classification.- Multi-grained Aspect Fusion for Review Response Generation.- Multiple Object Tracking based on Variable GIoU-Embedding Matrix and Kalman Filter Compensation.- Multi-relation Identification for Few-shot Document-level Relation Extraction.- Multi-Task Learning for Mongolian Morphological Analysis.- Multi-task Pre-training for Lhasa-Tibetan Speech Recognition.- Mutual Information Dropout: Mutual Information Can  Be All You Need.- Non-Outlier Pseudo-Labeling for Short Text Clustering.- Optimal Node Embedding Dimension Selection Using Overall Entropy.- PairEE: A Novel Pairing-Scoring Approach for Better Overlapping Event Extraction.- PCB Component Rotation Detection Based on Polarity Identifier Attention.- PCDialogEval: Persona and Context Aware EmotionalDialogue Evaluation.- PlantDet: A benchmark for Plant Detection in the Three-Rivers-Source Region.- PO-DARTS: Post-Optimizing the Architectures Searched by Differentiable Architecture Search Algorithms.- Predicting high vs low mother-baby synchrony with GRU-based ensemble models.- Properties of the weighted and robust implicitly weighted correlation coefficients.- PSML: Prototype-Based OSSL Framework for Multi-Information Mining.- Pure Physics-Informed Echo State Network of ODE Solution Replicator.- RegionRel:A Framework for Jointly Extracting Relational Triplets by Performing Sub-tasks by Region.- Robustness to Variability and Asymmetry of In-memory On-chip Training.- Selecting Distinctive-Variant Training Samples Base on Intra-class Similarity.- Semantic Information Mining and Fusion Method for Bot Detection.- Semilayer-Wise Partial Quantization without Accuracy Degradation or Back Propagation.- ShadowGAN for Line Drawings Shadow Generation.- Ship Attitude Prediction Based on Dynamic Sliding Window and EEMD-SSA-BiLSTM.- Solving Math Word Problem with External Knowledge and Entailment Loss.- Spatially Invariant and Frequency-Aware CycleGAN for Unsupervised MR-to-CT Synthesis.- Spatio-temporal Attention Model with Prior Knowledge for Solar Wind Speed Prediction.- Spatiotemporal model with attention mechanism for ENSO Predictions.- SPM-Diffusion for Temperature Prediction.- S-SOLVER: Numerically stable adaptive step size solver for neural ODEs.- TableSF: A Structural Bias Framework for Table-to-Text Generation.- TCS-LipNet:Temporal & Channel & Spatial Attention-based Lip Reading Network.- The Dynamic Selection of Combination Methods in Classifier Ensembles by Region of Competence.- The progressive detectors and discriminative feature descriptors combining global and local information.- Towards Better Dialogue Utterance Rewriting via a Gated Span-Copy Mechanism.- TSP Combination Optimization with Semi-local Attention Mechanism.- UDCGN: Uncertainty-Driven Cross-Guided Network for Depth Completion of Transparent Objects.- Use of Machine Learning Algorithms to Analyze the Digit Recognizer Problem in an Effective Manner.- Vulnerability Analysis of Continuous Prompts for Pre-trained Language Models.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Zusatzinfo XXXIV, 523 p. 208 illus., 180 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 848 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Adversarial Neural Networks • artificial neural networks (NN) • Bioinformatics • convolutional neural networks • cybersecurity • Deep learning • federated learning • graph clustering • graph neural networks • image-video analysis • machine learning • natural language • Object detection • Optimization • Recurrent Neural Networks • Text Mining • Timeseries
ISBN-10 3-031-44200-8 / 3031442008
ISBN-13 978-3-031-44200-1 / 9783031442001
Zustand Neuware
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