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PRICAI 2022: Trends in Artificial Intelligence: 19th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2022, Shanghai, China, November 1013, 2022, Proceedings, Part III 1st ed. 2022 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 650 pages, height x width: 235x155 mm, weight: 1015 g, 216 Illustrations, color; 8 Illustrations, black and white; XXI, 650 p. 224 illus., 216 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 13631
  • Izdošanas datums: 04-Nov-2022
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031208676
  • ISBN-13: 9783031208676
  • Mīkstie vāki
  • Cena: 91,53 €*
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  • Formāts: Paperback / softback, 650 pages, height x width: 235x155 mm, weight: 1015 g, 216 Illustrations, color; 8 Illustrations, black and white; XXI, 650 p. 224 illus., 216 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 13631
  • Izdošanas datums: 04-Nov-2022
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031208676
  • ISBN-13: 9783031208676
This three-volume set, LNAI 13629, LNAI 13630, and LNAI 13631 constitutes  the thoroughly refereed proceedings of the 19th Pacific Rim Conference on Artificial Intelligence, PRICAI 2022, held in Shangai, China, in November 10–13, 2022.

The 91 full papers and 39 short papers presented in these volumes were carefully reviewed and selected from 432 submissions. PRICAI covers a wide range of topics in the areas of social and economic importance for countries in the Pacific Rim: artificial intelligence, machine learning, natural language processing, knowledge representation and reasoning, planning and scheduling, computer vision, distributed artificial intelligence, search methodologies, etc.
Recommender System.- Mixture of Graph Enhanced Expert Networks for
Multi-task Recommendation.- MF-TagRec: Multi-feature fused tag recommendation
for GitHub.- Co-contrastive Learning for Multi-behavior
Recommendation.- Pattern Matching and Information-aware between Reviews
and Ratings for Recommendation.- Cross-view Contrastive Learning for
Knowledge-aware Session-based Recommendation.- Reinforcement Learning.- HiSA:
Facilitating Efficient Multi-Agent Coordination and Cooperation by
Hierarchical Policy with Shared Attention.- DDMA: Discrepancy-Driven
Multi-Agent Reinforcement Learning.- PRAG: Periodic Regularized Action
Gradient for Efficient Continuous Control.- Identifying Multiple Influential
Nodes for Complex Networks based on Multi-Agent Deep Reinforcement
Learning.- Online Learning in Iterated Prisoners Dilemma to Mimic Human
Behavior.- Optimizing Exploration-Exploitation Trade-off in Continuous Action
Spaces via Q-ensemble.- Hidden Information General Game Playing With Deep
Learning and Search.- Sequential Decision Making with Sequential
Information in Deep Reinforcement
Learning.- Two-Stream Communication-Efficient Federated Pruning
Network.- Strong General AI.- Multi-scale Lightweight Neural Network for
Real-time Object Detection.- Hyperspectral Image Classification Based On
Transformer and Generative Adversarial Network.- Deliberation Selector for
Knowledge-grounded Conversation Generation.- Training a Lightweight ViT
Network for Image Retrieval.- Vision and Perception.- Segmentedoriginal
Image Pairs to Facilitate Feature Extraction in Deep Learning Models.-
FusionSeg: Motion Segmentation by Jointly Exploiting Frames and
Events.- Weakly-supervised Temporal Action Localization with Multi-head
Cross-modal Attention.- CrGAN: Continuous Rendering of Image Style.- DPCN:
Dual Path Convolutional Network for Single Image Deraining.- All Up to You:
Controllable Video Captioning With a Masked Scene Graph.- A Multi-Head
Convolutional Neural Network With Multi-path Attention improves Image
Denoising.- Learning Spatial Fusion and Matching for Visual Object
Tracking.- Lightweight Wavelet-based Transformer for Image Super-resolution.-
Efficient high-resolution human pose estimation.- The Geometry Enhanced Deep
Implicit Function based 3D Reconstruction for objects in a real-scene
image.- Multi-View Stereo Network with Attention Thin Volume.- 3D Point Cloud
Segmentation Leveraging Global 2D-view Features.- Self-Supervised
Indoor 360-Degree Depth Estimation via Structural Regularization.- Global
Boundary Refinement for Semantic Segmentation via Optimal
Transport.- Optimization-based Predictive Approach for On-Demand 
Transportation.- JointContrast: Skeleton-based Mutual Action Recognition with
Contrastive Learning.- Nested Multi-Axis Learning Network for Single
Image Super Resolution.- Efficient Scale Divide and Conquer Network for
Object Detection.- Video-Based Emotion Recognition in the Wild for Online
Education Systems.- Real-world Underwater Image Enhancement via
Degradation-aware Dynamic Network.- Self-Supervised Vision Transformer based
Nearest Neighbor Classification for Multi-Source Open-Set Domain
Adaptation.- Lightweight image dehazing neural network model based on
estimating medium transmission map by intensity.- CMNet: Cross-aggregation
Multi-branch Network for Salient Object Detection.- More than Accuracy: an
Empirical Study of Consistency between Performance and
Interpretability.- Object-scale Adaptive Optical Flow Estimation Network.- A
Task-aware Dual Similarity Network for Fine-grained Few-shot
Learning.- Rotating Target Detection Based On Lightweight Network.- Corner
Detection Based on a Dynamic Measure of Cornerity.