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Fast Global Image Smoothing via Quasi Weighted Least Squares
Image smoothing is a long-studied research area with tremendous approaches proposed. However, how to perform high-quality image smoothing with less...
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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
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LV-YOLO: logistic vehicle speed detection and counting using deep learning based YOLO network
In the era of smart cities and advancing transportation technologies, predicting logistic vehicle and vehicle speed is pivotal to enhancing traffic...
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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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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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The Multi-attribute impact of hyperlinks in blogs: an emotion-centric approach
As a digital social medium, blogs have transformed into arenas where individuals can express their perspectives, concepts, and feelings. This...
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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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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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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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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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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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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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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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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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Building RadiologyNET: an unsupervised approach to annotating a large-scale multimodal medical database
BackgroundThe use of machine learning in medical diagnosis and treatment has grown significantly in recent years with the development of...
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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...