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Fabric image retrieval based on multi-modal feature fusion
With the increasing of multi-source heterogeneous data, flexible retrieval across different modalities is an urgent demand in industrial...
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Joint and Individual Feature Fusion Hashing for Multi-modal Retrieval
Unsupervised multi-modal hashing has received considerable attention in large-scale multimedia retrieval areas since its low storage and high search...
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A robot gras** detection network based on flexible selection of multi-modal feature fusion structure
In unstructured scenarios, objects usually have unique shapes, poses, and other uncertainties, which put forward higher requirements for the robot’s...
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PCDR-DFF: multi-modal 3D object detection based on point cloud diversity representation and dual feature fusion
Recently, multi-modal 3D object detection techniques based on point clouds and images have received increasing attention. However, existing methods...
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Unsupervised RGB-T object tracking with attentional multi-modal feature fusion
RGB-T tracking means that given the object position in the first frame, the tracker is trained to predict the position of the object in consecutive...
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AMFF-net: adaptive multi-modal feature fusion network for image classification
Convolutional neural networks(CNNs) have been applied to different computer vision tasks such as image classification and recognition, object...
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Semantic2Graph: graph-based multi-modal feature fusion for action segmentation in videos
Video action segmentation have been widely applied in many fields. Most previous studies employed video-based vision models for this purpose....
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Human risky behaviour recognition during ladder climbing based on multi-modal feature fusion and adaptive graph convolutional network
Human falls during ladder climbing are typically instantaneous, making the timely and accurate determination of security risks during ladder climbing...
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Multi-modal bilinear fusion with hybrid attention mechanism for multi-label skin lesion classification
Skin cancer is one of the most prevalent malignancies in the world. Deep learning-based methods have been successfully used for skin disease...
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Feature Disentanglement and Adaptive Fusion for Improving Multi-modal Tracking
Multi-modal tracking has increasingly gained attention due to its superior accuracy and robustness in complex scenarios. The primary challenges in...
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ARF-Net: a multi-modal aesthetic attention-based fusion
Over the last decade, Online Social Media platforms have witnessed a dramatic expansion due to the substantial reliance of individuals on these...
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Online video visual relation detection with hierarchical multi-modal fusion
With the development of artificial intelligence technology, visual scene understanding has become a hot research topic. Online visual relation...
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Human Gait Recognition Based on Frontal-View Walking Sequences Using Multi-modal Feature Representations and Learning
Despite that much progress has been reported in gait recognition, most of these existing works adopt lateral-view parameters as gait features, which...
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Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation
In the daily application of an iris-recognition-at-a-distance (IAAD) system, many ocular images of low quality are acquired. As the iris part of...
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Lightweight network-based multi-modal feature fusion for face anti-spoofing
Effectively identifying attacked faces is an urgent problem to be solved in the scenario of face recognition. As deep learning is applied to face...
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MADMM: microservice system anomaly detection via multi-modal data and multi-feature extraction
Accurately detecting anomalies in microservice systems is crucial to avoid system failures and economic losses for users. Existing approaches detect...
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Multi-Modal Meta-Transfer Fusion Network for Few-Shot 3D Model Classification
Nowadays, driven by the increasing concern on 3D techniques, resulting in the large-scale 3D data, 3D model classification has attracted enormous...
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Multi-modal Domain Adaptation Method Based on Parameter Fusion and Two-Step Alignment
Due to the well-known domain shift problem, directly deploying a trained multi-modal classifier to a new environment usually leads to poor...
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Multi-modal hierarchical fusion network for fine-grained paper classification
Because huge amount of scientific papers have been published at an accelerating rate, it is beneficial to do intelligent paper classification,...
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Human activity recognition based on multi-modal fusion
In recent years, human activity recognition (HAR) methods are develo** rapidly. However, most existing methods base on single input data modality,...
