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CTL-I: Infrared Few-Shot Learning via Omnidirectional Compatible Class-Incremental
Accommodating infrared novel class in deep learning models without sacrificing prior knowledge of base class is a challenging task , especially when...
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A total variation global optimization framework and its application on infrared and visible image fusion
The main bottleneck faced by total variation methods for image fusion is that it is difficult to design a novel optimization model that can be solved...
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Fusion of near-infrared and visible light images under hazy environment using multiplicative dark channel prior
Haze and fog in outdoor environments cause contrast degradation in images. Either a single image or a pair of visible and near-infrared (NIR) images...
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Infrared and Visible Image Fusion Based on Multi-scale Gaussian Rolling Guidance Filter Decomposition
With the development of multi-source detectors, the fusion of infrared and visible light images has received close attention from researchers....
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Fall detection on embedded platform using infrared array sensor for healthcare applications
Previous vision-based research has predominantly used common visible light cameras as sensors for detecting falls in home environments. While some...
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Environment enhanced fusion of infrared and visible images based on saliency assignment
Among existing region-based infrared (IR) and visible (VIS) fusion methods, source images are segmented into thermal targets and backgrounds....
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Embedded real-time infrared and visible image fusion for UAV surveillance
Infrared and visible image fusion is a beneficial processing task for Unmanned Aerial Vehicle (UAV) surveillance, which can improve visibility by...
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Enhancing infrared images via multi-resolution contrast stretching and adaptive multi-scale detail boosting
Infrared imaging technology has attracted numerous interests in military, security, transportation, etc. However, infrared images suffer from low...
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Thermal infrared and visible sequences tracking via dual adversarial pixel fusion
Due to the strong complementary strengths of visible light and thermal infrared light, to overcome the limitations of visible light imaging,...
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Visible-infrared person re-identification via specific and shared representations learning
The primary goal of visible-infrared person re-identification (VI-ReID) is to match pedestrian photos obtained during the day and night. The majority...
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SACA-fusion: a low-light fusion architecture of infrared and visible images based on self- and cross-attention
Visible-infrared image fusion cannot only reveal respective features of multiband imaging but also combine complementary information. It thus...
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Global-to-Local Feature Mining Network for RGB-Infrared Person Re-Identification
RGB-Infrared person Re-Identification (RGB-IR ReID) is a challenging matching task that retrieves a RGB/infrared pedestrian image from the existing...
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Recent advances via convolutional sparse representation model for pixel-level image fusion
Image fusion aims to integrate complementary information from different source images into the final output image. This plays a significant role in...
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Infrared Aircraft Anti-interference Recognition Based on Feature Enhancement CenterNet
Infrared imaging guided air to air missile is a typical infrared imaging guided weapon system. In the process of attacking targets such as fighter...
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DRB-Net: Dilated Residual Block Network for Infrared Image Restoration
Infrared (IR) spectroscopic imaging offers label-free visualization of sample heterogeneity via spatially localized chemical information. This...
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High-Resolution Feature Representation Driven Infrared Small-Dim Object Detection
Infrared small-dim object detection is a challenging task due to the small size, weak features, lack of prominent structural information, and...
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Beyond a strong baseline: cross-modality contrastive learning for visible-infrared person re-identification
Cross-modality pedestrian image matching, which entails the matching of visible and infrared images, is a vital area in person re-identification...
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Dual Attention Feature Fusion for Visible-Infrared Object Detection
Feature fusion is an essential component of multimodal object detection to exploit the complementary information and common information between...
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Optimizing U-Net CNN performance: a comparative study of noise filtering techniques for enhanced thermal image analysis
Infrared thermal imaging presents a promising avenue for detecting physiological phenomena such as hot flushes in animals, presenting a non-invasive...
