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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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Image Segmentation Techniques for Intelligent Monitoring of Putonghua Examinations
Advances in Mathematical Physics, 2022 Image recognition and image processing usually contain the technique of image segmentation. Excellent segmentation results can directly affect the accuracy of image recognition and processing. The essence of image segmentation is to segment each frame of
Hui Liu
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An improved image segmentation algorithm based on the maximum class variance method [PDF]
MATEC Web of Conferences, 2020 Image segmentation is an important part of image processing. The result of image segmentation directly affects the effect of subsequent image processing. However the efficiency of the traditional maximum class variance method is low.
Qi Qianhui, Tian Yimin, Han Lili
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UNet++: A Nested U-Net Architecture for Medical Image Segmentation [PDF]
DLMIA/ML-CDS@MICCAI, 2018 In this paper, we present UNet++, a new, more powerful architecture for medical image segmentation. Our architecture is essentially a deeply-supervised encoder-decoder network where the encoder and decoder sub-networks are connected through a series of ...
Zongwei Zhou +3 more
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TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation [PDF]
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2021 Medical image segmentation - the prerequisite of numerous clinical needs - has been significantly prospered by recent advances in convolutional neural networks (CNNs). However, it exhibits general limitations on modeling explicit long-range relation, and
Yundong Zhang, Huiye Liu, Qiang Hu
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UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation [PDF]
IEEE Transactions on Medical Imaging, 2019 The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN). Despite their success, these models have two limitations: (1) their optimal depth is apriori unknown, requiring extensive ...
Zong-Wei Zhou +3 more
semanticscholar +1 more source
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation [PDF]
Medical Image Analysis, 2023 The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation tasks and its prompt-based interface.
Jun-De Wu +7 more
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A Method of Polished Rice Image Segmentation Based on YO-LACTS for Quality Detection
Agriculture, 2023 The problem of small and multi-object polished rice image segmentation has always been one of importance and difficulty in the field of image segmentation.
Jinbo Zhou +5 more
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UNeXt: MLP-based Rapid Medical Image Segmentation Network [PDF]
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2022 UNet and its latest extensions like TransUNet have been the leading medical image segmentation methods in recent years. However, these networks cannot be effectively adopted for rapid image segmentation in point-of-care applications as they are parameter-
Jeya Maria Jose Valanarasu +1 more
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Sensors, 2021 High-spatial-resolution images play an important role in land cover classification, and object-based image analysis (OBIA) presents a good method of processing high-spatial-resolution images.
Shuang Hao, Yuhuan Cui, Jie Wang
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