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Survey of Image Edge Detection
Frontiers in Signal Processing, 2022 Edge detection technology aims to identify and extract the boundary information of image pixel mutation, which is a research hotspot in the field of computer vision.
Rui Sun +12 more
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Metasurface enabled broadband all optical edge detection in visible frequencies. [PDF]
Nat Commun, 2023 Image processing is of fundamental importance for numerous modern technologies. In recent years, due to increasing demand for real-time and continuous data processing, metamaterial and metasurface based all-optical computation techniques emerged as a ...
Tanriover I, Dereshgi SA, Aydin K.
europepmc +2 more sources
Edge Detection of Motion-Blurred Images Aided by Inertial Sensors [PDF]
Sensors, 2023 Edge detection serves as the foundation for advanced image processing tasks. The accuracy of edge detection is significantly reduced when applied to motion-blurred images.
Luo Tian +3 more
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Edge detection with meta-lens: from one dimension to three dimensions
Nanophotonics, 2021 Meta-lens has successfully been developed for a variety of optical functions. We demonstrate a light-field edge detection imaging system with a gallium nitride achromatic meta-lens array.
Chen Mu Ku +7 more
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Low-power edge detection based on ferroelectric field-effect transistor [PDF]
Nature CommunicationsEdge detection is one of the most essential research hotspots in computer vision and has a wide variety of applications, such as image segmentation, target detection, and other high-level image processing technologies.
Jiajia Chen +16 more
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Pixel Difference Networks for Efficient Edge Detection [PDF]
IEEE International Conference on Computer Vision, 2021 Recently, deep Convolutional Neural Networks (CNNs) can achieve human-level performance in edge detection with the rich and abstract edge representation capacities.
Z. Su +7 more
semanticscholar +1 more source
Refined Edge Detection Method Based on Semantic Information [PDF]
Jisuanji gongcheng, 2022 Edge detection is to accurately extract visually significant edge pixels from the image to obtain the edge information of the image.Traditional edge detection methods based on Full Convolution Network(FCN) usually require rough and fuzzy edge prediction ...
HUANG Sheng, RAN Haoshan
doaj +1 more source
Tiny and Efficient Model for the Edge Detection Generalization [PDF]
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2023 Most high-level computer vision tasks rely on low-level image operations as their initial processes. Operations such as edge detection, image enhancement, and super-resolution, provide the foundations for higher level image analysis.
Xavier Soria Poma +3 more
semanticscholar +1 more source
EDTER: Edge Detection with Transformer [PDF]
Computer Vision and Pattern Recognition, 2022 Convolutional neural networks have made significant progresses in edge detection by progressively exploring the context and semantic features. However, local details are gradually suppressed with the enlarging of receptive fields.
Mengyang Pu +4 more
semanticscholar +1 more source
Dense Extreme Inception Network for Edge Detection [PDF]
Pattern Recognition, 2021 . Edge detection is the basis of many computer vision applications. State of the art predominantly relies on deep learning with two decisive factors: dataset content and network's architecture.
Xavier Soria Poma +3 more
semanticscholar +1 more source