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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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End-to-End Video Text Spotting with Transformer
Recent video text spotting methods usually require the three-staged pipeline, i.e., detecting text in individual images, recognizing localized text,...
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Multi-modal Prototypes for Open-World Semantic Segmentation
In semantic segmentation, generalizing a visual system to both seen categories and novel categories at inference time has always been practically...
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3D Reconstruction of flame temperature field based on lightweight residual network with spatial attention mechanism
Flame temperature field measurement has always been a key topic in combustion research, which is of great significance for combustion state diagnosis...
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Reduction of the noise effects in phase images using a motorized dual-wavelength quantitative phase microscope
This article introduces a novel method that leads to the reduction of noise effects and improvement in the quality of phase image acquisition in...
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CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement
Image color difference (CD) measurement, a crucial concept in color science and imaging technology, aims to quantify the perceived difference between...
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Learning Feature Restoration Transformer for Robust Dehazing Visual Object Tracking
In recent years, deep-learning-based visual object tracking has obtained promising results. However, a drastic performance drop is observed when...
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Learning to sculpt neural cityscapes
We introduce a system that learns to sculpt 3D models of massive urban environments. The majority of humans live their lives in urban environments,...
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Intelligent Personality Assessment and Verification from Handwriting using Machine Learning
It is possible to tell a lot about a person just by looking at their handwriting. The way someone writes might tell you a lot about who, they are as...
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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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Improving laryngeal cancer detection using chaotic metaheuristics integration with squeeze-and-excitation resnet model
Laryngeal cancer (LC) represents a substantial world health problem, with diminished survival rates attributed to late-stage diagnoses. Correct...
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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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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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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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A full-detection association tracker with confidence optimization for real-time multi-object tracking
Multi-object tracking (MOT) aims to obtain trajectories with unique identifiers for multiple objects in a video stream. In current approaches,...
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Multi-source-free Domain Adaptive Object Detection
To enhance the transferability of object detection models in real-world scenarios where data is sampled from disparate distributions, considerable...
