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Produktbild: PRICAI 2022: Trends in Artificial Intelligence
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PRICAI 2022: Trends in Artificial Intelligence 19th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2022, Shanghai, China, November 10–13, 2022, Proceedings, Part II

Aus der Reihe Lecture Notes in Computer Science
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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.11.2022

Herausgeber

Sankalp Khanna + weitere

Verlag

Springer

Seitenzahl

546

Maße (L/B/H)

23,5/15,5/3,1 cm

Gewicht

850 g

Auflage

1st edition 2022

Sprache

Englisch

ISBN

978-3-031-20864-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.11.2022

Herausgeber

Verlag

Springer

Seitenzahl

546

Maße (L/B/H)

23,5/15,5/3,1 cm

Gewicht

850 g

Auflage

1st edition 2022

Sprache

Englisch

ISBN

978-3-031-20864-5

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: PRICAI 2022: Trends in Artificial Intelligence
  • Knowledge Representation and Reasoning .- Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information.- Source-Free Implicit Semantic Augmentation for Domain Adaptation.- Role-Oriented Network Embedding Method Based on Local Structural Feature and Commonality.- Dynamic Refining Knowledge Distillation Based on Attention Mechanism.-  Entity Representation by Neighboring Relations Topology for Inductive Relation Prediction.- Entity Similarity-based Negative Sampling for Knowledge Graph Embedding.- Label Enhancement using Inter-Example Correlation Information.- Link Prediction via Fused Attribute Features Activation with Graph Convolutional Network.- Multi-Subspace Attention Graph Pooling.- Embedding for Temporal Knowledge Graph Reasoning.-  Natural Language Processing .- M2FNet: Multi-granularity Feature Fusion Network for Medical Visual Question Answering.- Noise-robust Semi-supervised Multi-modal Machine Translation.- SETFF: A Semantic Enhanced Table Filling Framework for Joint Entity and Relation Extraction.- PEKIN: Prompt-based External Knowledge Integration Network for Rumor Detection on Social Media.-  Entity-aware Social Media Reading Comprehension.- Analysis via Virtual Node Augmented Graph Convolutional Networks.- Bidirectional Macro-level Discourse Parser based on Oracle Selection.- Evidence-Based Document-Level Event Factuality Identification.- Named Entity Recognition Model of Power Equipment Based on Multi-feature Fusion.- Improving Abstractive Multi-document Summarization with Predicate-Argument Structure Extraction.- A Structure-aware Method for Cross-domain Text Classification.- SICM: A Supervised-based Identification and Classification Model for Chinese Jargons Using Feature Adapter Enhanced BERT.- HS2N: Heterogeneous Semantics-Syntax Fusion Network for Document-level Event Factuality Identification.-  Pay Attention to the ”Tails”: A Novel Aspect-Fusion Model for Long-Tailed Aspect Category Detection.- Choice-driven Contextual Reasoning for Commonsense Question Answering.- Implicit Discourse Relation Recognition Based on Multi-granularity Context Fusion Mechanism.- Chinese Medical Named Entity Recognition Using External Knowledge.-  Neural Networks and Deep Learning .- Trajectory Prediction With Heterogeneous Graph Neural Network.- EEF1-NN: Efficient and EF1 allocations through Neural Networks.- Weighted Adaptive Perturbations Adversarial Training for Improving Robustness.- Improved Network Pruning via Similarity-Based Regularization.- Dynamic-GTN: Learning an Node Efficient Embedding in Dynamic Graph with Transformer.- ICDT: Incremental Context Guided Deliberation Transformer for Image Captioning.- Semantic-Adversarial Graph Convolutional Network for Zero-shot Cross-modal Retrieval.- DAST: Depth-Aware Assessment and Synthesis Transformer for RGB-D Salient Object Detection.-  A Vehicle Re-ID Algorithm Based on Channel Correlation Self-Attention and Lstm Local Information Loss.-  A Self-Supervised Graph Autoencoder with Barlow Twins.- Few-shot Image Classification Method Based on Fusion of Important Features of Different Scales.-  Group Residual Dense Block for Key-Point Detector with One-level Feature.