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Chapter and Conference Paper
Text-Oriented Modality Reinforcement Network for Multimodal Sentiment Analysis from Unaligned Multimodal Sequences
Multimodal Sentiment Analysis (MSA) aims to mine sentiment information from text, visual, and acoustic modalities. Previous works have focused on representation learning and feature fusion strategies. However,...
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Article
Open AccessA method for evaluating the learning concentration in head-mounted virtual reality interaction
In education, learning concentration is closely related to the quality of learning, and teachers can adjust their teaching methods accordingly to improve the learning outcomes of students. Particularly in head...
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Chapter and Conference Paper
Human-Object Interaction Detection: A Survey of Deep Learning-Based Methods
In recent years, rapid progress has been made in detecting and identifying single object instances. In order to understand the situation in the scene, computers need to recognize how humans interact with surro...
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Chapter and Conference Paper
3D Face Cartoonizer: Generating Personalized 3D Cartoon Faces from 2D Real Photos with a Hybrid Dataset
Cartoon face is a prevalent kind of stylized face, which is widely used in movies, TVs and advertisements. Although plenty of methods have been proposed to generate 2D cartoon faces, it is still challenging to...
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Chapter and Conference Paper
LF-MAGNet: Learning Mutual Attention Guidance of Sub-Aperture Images for Light Field Image Super-Resolution
Many light field image super-resolution networks are proposed to directly aggregate the features of different low-resolution sub-aperture images (SAIs) to reconstruct high-resolution sub-aperture images. Howev...
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Chapter and Conference Paper
Scale-Aware Distillation Network for Lightweight Image Super-Resolution
Many lightweight models have achieved great progress in single image super-resolution. However, their parameters are still too many to be applied in practical applications, and it still has space for parameter...
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Chapter and Conference Paper
Learning Multi-level Interaction Relations and Feature Representations for Group Activity Recognition
Group activity recognition is an challenging task with a major issue that reasons about complex interaction relations in the context of multi-person scenes. Most existing approaches concentrate on capturing in...
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Chapter and Conference Paper
Study on Operation Strategy of Thermal Storage in Thermal Power Plant Based on Continuous Discrete Hybrid Control Method
With the continuous growth of power peak load and the rapid development of distributed new energy, the difficulty of power grid dispatching operation is increased, which poses a new major challenge to the powe...
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Chapter and Conference Paper
Investigating the 3D Local Myocytes Arrangement in the Human LV Mid-Wall with the Transverse Angle
Myolaminar Layer Arrangement plays an essential role in cardiac biomechanics. In this preliminary study, we investigate the local 3D arrangement of the myocytes inside the sheets (layers) in three LV human he...
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Chapter and Conference Paper
The Study and Application of Adaptive Learning Method Based on Virtual Reality for Engineering Education
As educational reform efforts continue, a challenge for most adaptive learning software is how to integrate theoretical knowledge with practice, especially in the field of engineering education. Develo** an ...
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Chapter and Conference Paper
SAF: Semantic Attention Fusion Mechanism for Pedestrian Detection
Benefiting from deep learning methods, pedestrian detection has witnessed a great progress in recent years. However, many pedestrian detectors are prone to detect background instances, especially under urban s...
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Chapter and Conference Paper
A Hyper Heuristic Algorithm for Low Carbon Location Routing Problem
In this paper, the carbon emission factor is taken into account in the Location Routing Problem (LRP), and a multi-objective LRP model combining carbon emission with total cost is established. Due to the compl...
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Chapter and Conference Paper
Improving Deep Crowd Density Estimation via Pre-classification of Density
Previous works about deep crowd density estimation usually chose one unified neural network to learn different densities. However, it is hard to train a compact neural network when the crowd density distributi...