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OverviewFull Product DetailsAuthor: Sankalp Khanna , Jian Cao , Quan Bai , Guandong XuPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 1st ed. 2022 Volume: 13631 Weight: 1.015kg ISBN: 9783031208676ISBN 10: 3031208676 Pages: 650 Publication Date: 04 November 2022 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsRecommender 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 Prisoner's 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.- Segmented-original 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.- Joint Contrast: 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.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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