Results 31 to 40 of about 6,313,537 (354)
Research on edge detection algorithm based on improved sobel operator [PDF]
MATEC Web of Conferences, 2020 In order to solve the shortcomings of traditional Sobel edge detection operator, such as low accuracy of image edge location and rough edge extracted, an improved edge detection algorithm based on Sobel operator is proposed. Firstly, in the aspect of the
Han Lili, Tian Yimin, Qi Qianhui
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Edge-Detect: Edge-Centric Network Intrusion Detection using Deep Neural Network [PDF]
2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), 2021 Edge nodes are crucial for detection against multitudes of cyber attacks on Internet-of-Things endpoints and is set to become part of a multi-billion industry. The resource constraints in this novel network infrastructure tier constricts the deployment of existing Network Intrusion Detection System with Deep Learning models (DLM). We address this issue
Singh, Praneet +3 more
openaire +2 more sources
Sobel Edge Detection Based on Weighted Nuclear Norm Minimization Image Denoising
Electronics, 2021 As a classic and effective edge detection operator, the Sobel operator has been widely used in image segmentation and other image processing technologies. This operator has obvious advantages in the speed of extracting the edge of images, but it also has
Run Tian +3 more
semanticscholar +1 more source
EVALUATION OF IMPROVED FUZZY INFERENCE SYSTEM TO PRESERVE IMAGE EDGE FOR IMAGE ANALYSIS
ICTACT Journal on Image and Video Processing, 2021 There are numerous applications based on edge detection have been used in the area of image analysis. The technique of edge detection is an important step towards the visual system reliability and security that delivers a better understanding in many ...
Manu Prakram +2 more
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Bi-Directional Cascade Network for Perceptual Edge Detection [PDF]
Computer Vision and Pattern Recognition, 2019 Exploiting multi-scale representations is critical to improve edge detection for objects at different scales. To extract edges at dramatically different scales, we propose a Bi-Directional Cascade Network (BDCN) structure, where an individual layer is ...
Jianzhong He +4 more
semanticscholar +1 more source
Edge information based object classification for NAO robots
Cogent Engineering, 2016 This paper presents a research regarding the development of a computationally cheap and reliable edge information based object detection and classification system for use on the NAO humanoid robots.
Karl Tarvas +2 more
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Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2019 This paper proposes a Deep Learning based edge detector, which is inspired on both HED (Holistically-Nested Edge Detection) and Xception networks. The proposed approach generates thin edge-maps that are plausible for human eyes; it can be used in any ...
Xavier Soria Poma, Edgar Riba, A. Sappa
semanticscholar +1 more source
Future Internet, 2022 With the wider adoption of edge computing services, intelligent edge devices, and high-speed V2X communication, compute-intensive tasks for autonomous vehicles, such as object detection using camera, LiDAR, and/or radar data, can be partially offloaded ...
Tianyu Bai, Song Fu, Qing Yang
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Edge detection algorithm of medical image based on Canny operator
Journal of Physics: Conference Series, 2021 Edge detection is an important part of image segmentation, in this paper, the edge detection algorithm based on traditional Canny operator for medical images is studied.
Ziqi Xu +3 more
semanticscholar +1 more source
SwinNet: Swin Transformer Drives Edge-Aware RGB-D and RGB-T Salient Object Detection [PDF]
IEEE transactions on circuits and systems for video technology (Print), 2022 Convolutional neural networks (CNNs) are good at extracting contexture features within certain receptive fields, while transformers can model the global long-range dependency features.
Zhengyi Liu +3 more
semanticscholar +1 more source