Results 21 to 30 of about 151,952 (268)
Superpixel Segmentation With Fully Convolutional Networks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 In computer vision, superpixels have been widely used as an effective way to reduce the number of image primitives for subsequent processing. But only a few attempts have been made to incorporate them into deep neural networks. One main reason is that the standard convolution operation is defined on regular grids and becomes inefficient when applied to
Fengting Yang +3 more
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Design and Analysis of VLAN-Driven Access Control and Secure Communication in Ring-Based Switched Networks [PDF]
ITM Web of ConferencesSecure access control and traffic separation is required today in order to allow networks to communicate securely and remain intact. In this paper we investigate how VLANs can be used as an effective method of creating logical access control and secure ...
S Chandrappa +5 more
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Co-optimization Learning Network for MRI Segmentation of Ischemic Penumbra Tissues
Frontiers in Neuroinformatics, 2021 Convolutional neural networks (CNNs) have brought hope for the medical image auxiliary diagnosis. However, the shortfall of labeled medical image data is the bottleneck that limits the performance improvement of supervised CNN methods.
Liangliang Liu +4 more
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Applied Sciences, 2022 Visual navigation is an important guidance method for industrial automated guided vehicles (AGVs). In the actual guidance, the overexposure environment may be encountered by the AGV lane image, which seriously reduces the accuracy of lane detection ...
Zongxin Yang +6 more
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A Lightweight Complex-Valued DeepLabv3+ for Semantic Segmentation of PolSAR Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Semantic image segmentation is one kindof end-to-end segmentation method which can classify the target region pixel by pixel. As a classic semantic segmentation network in optical images, DeepLabv3+ can achieve a good segmentation performance ...
Lingjuan Yu +6 more
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Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network
CoRR, 2018 Technical ...
de Geus, Daan +2 more
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DCSegNet: Deep Learning Framework Based on Divide-and-Conquer Method for Liver Segmentation
IEEE Access, 2020 Image segmentation plays a vital role in the medical diagnosis and intervention field. The segmentation methods can be classified as fully automated, semiautomated or manual.
Congsheng Li +6 more
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Weakly supervised skin lesion segmentation based on spot‐seeds guided optimal regions
IET Image Processing, 2023 Automatic skin lesion segmentation is the most critical and relevant task in computer‐aided skin cancer diagnosis. Methods based on convolutional neural networks (CNNs) are mainly used in current skin lesion segmentation.
Zaid Al‐Huda +4 more
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IEEE Access, 2021 Disease is one of the main factors affecting crop growth. How to reflect the external morphological features of the disease and completely retain the color and texture information of the disease area is one of the key research issues for crop disease ...
Yuxia Yuan, Zengyong Xu, Gang Lu
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Point Cloud Semantic Segmentation Method Based on Block Feature Fusion [PDF]
Jisuanji gongcheng, 2022 A semantic segmentation method integrating block features is proposed to reduce the computational complexity of semantic segmentation of multi-class 3D objects in outdoor large-scale point cloud scenes.The square grid segmentation method is used to ...
GAO Qingji, LI Tianhao, XING Zhiwei, LIU Peipei
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