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Detection of Moiré pattern in high-resolution images
Despite the improvements in the quality of digital images brought about by the development of digital cameras and smartphones, taking clean...
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Inverse Imaging: Reconstructing High-Resolution Images from Degraded Images
Inverse problems such as image denoising, super-resolution and image reconstruction are based on complex unsupervised machine learning techniques. We...
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Synthesizing multi-frame high-resolution fluorescein angiography images from retinal fundus images using generative adversarial networks
BackgroundFundus fluorescein angiography (FA) can be used to diagnose fundus diseases by observing dynamic fluorescein changes that reflect vascular...
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High-resolution brain tractography from X-ray phase-contrast images
X-ray phase contrast tomography (XPCT) can produce high contrast isotropic images of biological samples in only a few minutes thanks to the unique...
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Edge Map Extraction of High-Resolution Facial Images
This work focuses on edge detection, a vital task in several fields, such as computer vision, image processing, and pattern recognition. Since exact...
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Review of Building Extraction Methods Based on High-Resolution Remote Sensing Images
With the continuous advancement of the construction of smart cities, the efficient acquisition and automatic extraction of building information is...
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District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
This paper describes a dataset collected by infrared thermography, a non-contact, non-intrusive technique to acquire data and analyze the built...
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Leveraging high-resolution remote sensing images for vehicle type detection using sparrow search optimization with deep learning
High-resolution remote sensing images (RSI) refer to images captured from a distance, usually from an aircraft or satellite that provide details...
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Deep learning reconstruction for high-resolution computed tomography images of the temporal bone: comparison with hybrid iterative reconstruction
PurposeWe investigated whether the quality of high-resolution computed tomography (CT) images of the temporal bone improves with deep learning...
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Semantic Segmentation of High-Resolution Remote Sensing Images with Improved U-Net Based on Transfer Learning
Semantic segmentation of high-resolution remote sensing images has emerged as one of the foci of research in the remote sensing field, which can...
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Detection of Defects on Cut-Out Switches in High-Resolution Images Based on YOLOv5 Algorithm
The reliability of a cut-out switch (COS) directly affects the stable operation of electric power distribution systems. Detecting a defective COS...
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Water body extraction from high spatial resolution remote sensing images based on enhanced U-Net and multi-scale information fusion
Employing deep learning techniques for the semantic segmentation of remote sensing images has emerged as a prevalent approach for acquiring...
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High spatiotemporal-resolution map** for a seasonal erosion flooding inundation using time-series Landsat and MODIS images
Seasonal erosion flooding events present a significant challenge for effective disaster monitoring and land degradation studies. This research...
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Surface water extraction from high-resolution remote sensing images based on an improved U-net network model
This paper proposes a surface water extraction method from high-resolution remote sensing images based on an improved U-Net network model. The GF-6...
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Crop height estimation of sorghum from high resolution multispectral images using the structure from motion (SfM) algorithm
Crop height (CH) is the key indicators of crop growth, biomass and yield. However, obtaining CH information with manual measurement is inefficient...
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Refinement analysis of landslide risk assessment for wide area based on UAV-acquired high spatial resolution images
The Loess Plateau is the largest loess accumulation zone globally. It has a fragile geological and ecological environment, experiences significant...
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An improved semantic segmentation algorithm for high-resolution remote sensing images based on DeepLabv3+
High-precision and high-efficiency Semantic segmentation of high-resolution remote sensing images is a challenge. Existing models typically require a...
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Crop-Guided Neural Network Segmentation of High-Resolution Skin Lesion Images
Medical images are often exceedingly large in width and height, limiting the maximum batch size when training convolutional neural networks and...