Results 11 to 20 of about 6,662,539 (239)
Survey on Image Panoptic Segmentation Based on Deep Learning [PDF]
Jisuanji kexue yu tansuo, 2023 With the continuous development of deep learning and image segmentation, image panoptic segmentation has become a research hotspot in the field of computer vision, and many image panoptic segmentation methods have been proposed. This paper summarizes the
BI Yangyang, ZHENG Yuanfan, SHI Caijuan, ZHANG Kun, LIU Jian
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Survey Progress on Image Instance Segmentation Methods of Deep Convolutional Neural Network [PDF]
Jisuanji kexue, 2022 Image instance segmentation is an important part of image processing and computer vision technology about image understanding.With the development of deep learning and deep convolutional neural network,image instance segmentation method based on deep ...
HU Fu-yuan, WAN Xin-jun, SHEN Ming-fei, XU Jiang-lang, YAO Rui, TAO Zhong-ben
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Masked-attention Mask Transformer for Universal Image Segmentation [PDF]
Computer Vision and Pattern Recognition, 2021 Image segmentation groups pixels with different semantics, e.g., category or instance membership. Each choice of semantics defines a task. While only the semantics of each task differ, current research focuses on designing spe-cialized architectures for ...
Bowen Cheng +4 more
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UNETR: Transformers for 3D Medical Image Segmentation [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2021 Fully Convolutional Neural Networks (FCNNs) with contracting and expanding paths have shown prominence for the majority of medical image segmentation applications since the past decade. In FCNNs, the encoder plays an integral role by learning both global
Ali Hatamizadeh +3 more
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Segmentation for Athlete's Ankle Injury Image Using Residual Double Attention U-Net Model [PDF]
Brazilian Archives of Biology and Technology, 2023 The image of an athlete's ankle joint injury can help to check whether the athlete's ankle joint is damaged, and plays a very important role in clinical diagnosis.
Jing Zhang +3 more
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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.
Junde Wu +7 more
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Research Review of Image Semantic Segmentation Method in High-Resolution Remote Sensing Image Interpretation [PDF]
Jisuanji kexue yu tansuo, 2023 Rapid acquisition of remote sensing information has important research significance for the development of image semantic segmentation methods in remote sensing image interpretation applications.
MA Yan, Gulimila·Kezierbieke
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Customized Segment Anything Model for Medical Image Segmentation [PDF]
arXiv.org, 2023 We propose SAMed, a general solution for medical image segmentation. Different from the previous methods, SAMed is built upon the large-scale image segmentation model, Segment Anything Model (SAM), to explore the new research paradigm of customizing ...
Kaiwen Zhang, Dong Liu
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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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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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