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Enhancing signed social recommendation via extracting auxiliary textual information
Real-world applications are increasingly using personalized suggestions to guide users toward interesting content. Graphic Convolutional Neural...
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Hi-GNN: hierarchical interactive graph neural networks for auxiliary information-enhanced recommendation
Networked auxiliary information (e.g., user social network, item transition network, etc.) plays a significant role to alleviate the sparse...
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Multi-component graph collaborative filtering using auxiliary information for TV program recommendation
Recommendation systems for TV programs play an important role in alleviating the information overload problem. Existing TV program recommendation...
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Enhanced context-aware citation recommendation with auxiliary textual information based on an auto-encoding mechanism
The process of retrieving suitable papers which are related to an interesting topic while doing research normally takes a lot of time and effort....
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Auxiliary Information Enhanced Span-Based Model for Nested Named Entity Recognition
Span-based methods have unique advantages for solving nested named entity recognition (NER) problems. As primary information, boundaries play a...
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Vision Transformer with Depth Auxiliary Information for Face Anti-spoofing
Face anti-spoofing (FAS) is an important part of the face recognition system. Although methods based on convolutional neural networks (CNN) have...
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Multi-modal Recommendation System with Auxiliary Information
Context-aware recommendation systems improve upon classical recommender systems by including, in the modelling, a user’s behaviour. Research into...
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High-resolution network with an auxiliary channel for 2D hand pose estimation
High-resolution networks have been applied in various fields because of their advanced architecture. However, multiple multi-scale fusions of high...
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Learning multi-tasks with inconsistent labels by using auxiliary big task
Multi-task learning is to improve the performance of the model by transferring and exploiting common knowledge among tasks. Existing MTL works mainly...
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CAE-GReaT: Convolutional-Auxiliary Efficient Graph Reasoning Transformer for Dense Image Predictions
Convolutional Neural Networks (CNNs) and Vision Transformer (ViT) are two primary frameworks for current semantic image recognition tasks in the...
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Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker
Siamese-like trackers expose considerable shortcomings in the case of brief occlusion due mainly to the inadequate consideration of the correlation...
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Fragrant: frequency-auxiliary guided relational attention network for low-light action recognition
Video action recognition aims to classify actions within sequences of video frames, which has important applications in computer vision fields....
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Communication-robust multi-agent learning by adaptable auxiliary multi-agent adversary generation
Communication can promote coordination in cooperative Multi-Agent Reinforcement Learning (MARL). Nowadays, existing works mainly focus on improving...
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Dynamic context-driven progressive image inpainting with auxiliary generative units
Image inpainting aims to restore missing or damaged regions of an image with plausible visual content. Most existing methods always face challenges...
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Towards stronger illumination robustness of local feature detection and description based on auxiliary learning
Local feature detection and description play a crucial role in various computer vision tasks, including image matching. Variations in illumination...
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Sample-level weighting for multi-task learning with auxiliary tasks
Multi-task learning (MTL) can improve the generalization performance of neural networks by sharing representations with related tasks. Nonetheless,...
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Air combat maneuver decision based on deep reinforcement learning with auxiliary reward
For air combat maneuvering decision, the sparse reward during the application of deep reinforcement learning limits the exploration efficiency of the...
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Auxiliary feature extractor and dual attention-based image captioning
Currently, most image caption generation models use object features output from pre-trained detectors as input for multimodal learning of images and...
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PEDI-GAN: power equipment data imputation based on generative adversarial networks with auxiliary encoder
Smart grids commonly rely on analyzing sensor data to monitor power equipment. However, these sensor data can suffer varying levels of loss or...
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Pupil center detection inspired by multi-task auxiliary learning characteristic
Robust and accurate pupil center detection is a prerequisite for eye-tracking system. In natural environments, due to rapid illumination...
