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A triple fusion model for cross-modal deep hashing retrieval
In the field of resource retrieval, deep cross-modal retrieval is attracting increasing attention. It has a lower storage capacity and faster...
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Multi-level Self-supervised Representation Learning via Triple-way Attention Fusion and Local Similarity Optimization
Self-supervised image representation learning is centered on constructing general features with good quality from unlabeled images. However, most...
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A novel prostate segmentation method: triple fusion model with hybrid loss
Early and rapid diagnosis of prostate cancer, the horsehead disease among men, has become increasingly important. Nowadays, many methods are used in...
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TFM: A Triple Fusion Module for Integrating Lexicon Information in Chinese Named Entity Recognition
Due to the characteristics of the Chinese writing system, character-based Chinese named entity recognition models ignore the word information in...
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Video person re-identification based on RGB triple pyramid model
In order to solve the difficult problem of pedestrian motion extraction in video, in this paper, we propose a novel video action information...
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Deep Self-supervised Subspace Clustering with Triple Loss
Deep subspace clustering (DSC) methods are widely used in various fields such as motion segmentation, image segmentation, and text mining. It uses...
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Spatiotemporal heterogeneous information fusion model for loitering anomaly detection
In the field of video surveillance security in public places, loitering anomaly detection plays a crucial role. Currently, the complexity of public...
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Performance of representation fusion model for entity and relationship extraction within unstructured text
Automated identification of entities and their relationships from unstructured text is a critical aspect of information extraction. For this, joint...
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A Survey of Advanced Information Fusion System: from Model-Driven to Knowledge-Enabled
Advanced knowledge engineering (KE), represented by knowledge graph (KG), drives the development of various fields and engineering technologies and...
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Optimization of segmentation model based on maximization information fusion and its application in nuclear image analysis
The Whole Slide Image (WSI) is a pathological image with Hematoxylin & Eosin staining. The low-contrast color staining will bring a challenge on...
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Triple-channel graph attention network for improving aspect-level sentiment analysis
Aspect-level sentiment classification is a fine-grained sentiment analysis that primarily focuses on predicting the sentiment polarity of aspects...
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Triple-Path RNN Network: A Time-and-Frequency Joint Domain Speech Separation Model
Studies in speech separation have achieved significant success in recent years. To correctly separate the mixture signals, it is critical to encode...
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Dual-branch and triple-attention network for pan-sharpening
Pan-sharpening is a technique used to generate high-resolution multi-spectral (HRMS) images by merging high-resolution panchromatic (PAN) images with...
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Triple-level relationship enhanced transformer for image captioning
Region features and grid features are often used in the field of image captioning. As they are often extracted by different networks, fusing them for...
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TPN: Triple parts network for few-shot instance segmentation
Few-shot instance segmentation aims to segment unseen objects in a so-called query image, given only one close-up illustration named support image....
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A Multi-attention Triple Decoder Deep Convolution Network for Breast Cancer Segmentation Using Ultrasound Images
Breast cancer (BC) is a widely diagnosed deadly disease commonly present in middle-aged women around the globe. Ultrasound (U/S) imaging is widely...
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Multimodal image fusion on ECG signals for congestive heart failure classification
The electrocardiogram, or ECG, records electrical signals from the heart to detect various heart conditions. It helps in the diagnosis of important...
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Conjoined triple deep network for video anomaly detection
The video anomaly detection task typically involves identifying anomalous targets, behaviors, and events in surveillance using only normal samples....
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A focus fusion attention mechanism integrated with image captions for knowledge graph-based visual question answering
Visual question answering tasks based on the knowledge graph are dedicated to integrating rich information in the knowledge graph to deal with...
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Ternary symmetric fusion network for camouflaged object detection
Camouflage object detection (COD) is designed to locate objects that are “seamlessly” embedded in the surrounding environment. Camouflaged object...
