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Research on gesture segmentation method based on FCN combined with CBAM-ResNet50
As a key step of gesture recognition, gesture segmentation can effectively reduce the impact of complex backgrounds on recognition results and...
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Audio Transmission Based on Hybrid Crypto-steganography Framework for Efficient Cyber Security in Wireless Communication System
Wireless systems enable people in last decades to communicate and access applications and information without wires, which provided better image,...
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HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
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Adaptive shift graph convolutional neural network for hand gesture recognition based on 3D skeletal similarity
Graph convolutional neural networks (GCNs) have shown promising results in the field of hand gesture recognition based on 3D skeletal data. However,...
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M2AST:MLP-mixer-based adaptive spatial-temporal graph learning for human motion prediction
Human motion prediction is a challenging task in human-centric computer vision, involving forecasting future poses based on historical sequences....
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Lightweight model for small target detection of SAR images of ships based on NWD loss
Synthetic Aperture Radar (SAR) has the advantages of all-weather and high resolution, and is an effective tool for ship monitoring. SAR image ship...
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DiffCAS: diffusion based multi-attention network for segmentation of 3D coronary artery from CT angiography
Automatic segmentation of 3D coronary arteries from computed tomography angiography (CTA) is an indispensable part of accurate and efficient coronary...
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Image inpainting based on tensor ring decomposition with generative adversarial network
Image inpainting is a fundamental task in the field of computer vision. However, there are three major challenges associated with this technique: (1)...
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Progress on half a century of process modelling research in steelmaking: a review
Process modelling in steelmaking started from mid-sixties and witnessed rapid growth and wide spread applications during the last fifty years or so....
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Anomaly analytics in data-driven machine learning applications
Machine learning is used widely to create a range of prediction or classification models. The quality of the machine learning (ML) models depends not...
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MDEANet: modified detail-enhanced convolution and attention-based network for dehazing of remote sensing images
Image de-hazing aims to improve quality and restore clarity of hazy images. When airborne particles like dust and smoke absorb light, it can result...
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QuMIN: quantum multi-modal data fusion for humor detection
Humour detection has attracted considerable attention due to its significance in interpreting dialogues across text, visual, and acoustic modalities....
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The effect of interactive tutorial information and purpose built virtual chemistry laboratory on students’ performance
Different Virtual Chemistry Laboratories (VCLs) have been developed where users can perform their experimental work to increase their learning for...
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Using synthetic camera poses for camera calibration in soccer videos
Camera calibration is the process of estimating the parameters that describe the viewpoint of a camera. These parameters allow the map** of points...
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Hop**-mean: an augmentation method for motor activity data towards real-time depression diagnosis using machine learning
The advances from the last few decades in the fields of ML (Machine Learning), DL (Deep Learning), and semantic computing are now changing the shape...
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Temporal analysis of computational economics: a topic modeling approach
This study offers a comprehensive investigation into the thematic evolution within computational economics over the past two decades, leveraging...
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A combined non-convex TVp and wavelet \(\ell _1\)-norm approach for image deblurring via split Bregman method
Image deblurring is one of the most fundamental problems in the image processing and computer vision fields. The methods based on total variation are...
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Decentralized traffic management of autonomous drones
Coordination of local and global aerial traffic has become a legal and technological bottleneck as the number of unmanned vehicles in the common...
