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Image caption generation using Visual Attention Prediction and Contextual Spatial Relation Extraction
Automatic caption generation with attention mechanisms aims at generating more descriptive captions containing coarser to finer semantic contents in...
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Exploring Spatial Relation Awareness Through Virtual Indoor Environments
This research addresses the critical challenge of understanding spatial relations in virtual indoor environments. The proposed methodology comprises...
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A Joint Entity and Relation Extraction Approach Using Dilated Convolution and Context Fusion
In recent years, researchers have shown increasing interest in joint entity and relation extraction. However, existing approaches overlook the...
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APRE: Annotation-Aware Prompt-Tuning for Relation Extraction
Prompt-tuning has been successfully applied to support classification tasks in natural language processing and has achieved promising performance....
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Multi-perspective Feature Fusion for Event-Event Relation Extraction
Event-Event Relation Extraction (EERE) is a crucial task in the information extraction domain, which aims to obtain the relation between events and...
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Relation-Aware Facial Expression Recognition Using Contextual Residual Network with Attention Mechanism
With the existence of occlusion or posture changes, facial expression recognition (FER) under uncontrolled conditions is difficult. To obtain a...
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Entity Fusion Contrastive Inference Network for Biomedical Document Relation Extraction
In recent years, the field of biomedical information has experienced remarkable growth. Consequently, the extraction of semantic relationships...
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Joint relational triple extraction based on potential relation detection and conditional entity map**
Joint relational triple extraction treats entity recognition and relation extraction as a joint task to extract relational triples, and this is a...
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Contextual-wise discriminative feature extraction and robust network learning for subcortical structure segmentation
Robust and accurate segmentation of subcortical structures in MR images is difficult due to: (1) low image contrast and spatial resolution, (2)...
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Keypoint-based contextual representations for hand pose estimation
Most current methods for the hand pose estimation ignore the pixel-level relationship of hand keypoints, e.g. four specific keypoints in the same...
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Multi-head Attention and Graph Convolutional Networks with Regularized Dropout for Biomedical Relation Extraction
Automatic extraction of biomedical relation from text becomes critical because manual relation extraction requires significant time and resources....
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Attention-guided spatial–temporal graph relation network for video-based person re-identification
Video-based person Re-Identification (Re-ID) is to re-identify video tracklets belonging to a specific person when reviewing this person from...
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Entity relation joint extraction method for manufacturing industry knowledge data based on improved BERT algorithm
The existing joint extraction methods for entity relationships in knowledge data only target specific fields or datasets, which may have insufficient...
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Weighted graph convolution over dependency trees for nontaxonomic relation extraction on public opinion information
Currently, with the continuous development of relation extraction tasks, we notice that the ability to extract nontaxonomic relations has improved...
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Extraction and Visually Driven Analysis of VGI for Understanding People’s Behavior in Relation to Multifaceted Context
Volunteered Geographic Information in the form of actively and passively generated spatial content offers great potential to study people’s...
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A Multimodal Approach for Multiple-Relation Extraction in Videos
Automatically interpreting social relations, e.g., friendship, kinship, etc., from visual scenes has huge potential application value in areas such...
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Spatial-temporal graph-guided global attention network for video-based person re-identification
Global attention learning has been extensively applied in video-based person re-identification due to its superiority in capturing contextual...
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Relation-consistency graph convolutional network for image super-resolution
Convolutional neural networks (CNNs) have been widely exploited in single image super-resolution (SISR) due to their powerful feature representation...
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Automatic Generation of 3D Scene Animation Based on Dynamic Knowledge Graphs and Contextual Encoding
Although novel 3D animation techniques could be boosted by a large variety of deep learning methods, flexible automatic 3D applications (involving...
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Contextual transformer sequence-based recognition network for medical examination reports
The automatic recognition of the medical examination report table (MERT) is receiving increasing attention in recent years as it is an essential step...
