DCSLK: Combined large kernel shared convolutional model with dynamic channel Sampling
NeuroImageThis study centers around the competition between Convolutional Neural Networks (CNNs) with large convolutional kernels and Vision Transformers in the domain of computer vision, delving deeply into the issues pertaining to parameters and computational ...
Zongren Li +3 more
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Research of segmentation method on color image of Lingwu long jujubes based on the maximum entropy
EURASIP Journal on Image and Video Processing, 2017 This paper researches on methods of the color image segmentation method of Lingwu long jujubes based on the maximum entropy to achieve the accuracy of image segmentation and improve accuracy of machine recognition.
Yutan Wang +5 more
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Unsupervised image segmentation combining region and boundary estimation [PDF]
, 2001 An integrated approach to image segmentation is presented that combines region and boundary information using maximum a posteriori estimation and decision theory.
Bhalerao, Abhir +3 more
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2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 accepted to CVPR ...
Mina Ghadimi Atigh +4 more
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PointRend: Image Segmentation As Rendering [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 We present a new method for efficient high-quality image segmentation of objects and scenes. By analogizing classical computer graphics methods for efficient rendering with over- and undersampling challenges faced in pixel labeling tasks, we develop a unique perspective of image segmentation as a rendering problem.
Alexander Kirillov +3 more
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Review of Deep Learning Applications in Spinal Image Segmentation [PDF]
Jisuanji gongchengDeep learning algorithms have the advantages of strong learning, strong adaptive, and unique nonlinear mapping abilities in spinal image segmentation.
Baihao JIANG, Jing LIU, Dawei QIU, Liang JIANG
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Active contours based on weighted gradient vector flow and balloon forces for medical image segmentation [PDF]
, 2014 Active contours, or snakes, have been widely used for image segmentation purposes. However, high noise sensitivity and poor performance over weak edges are the most acute issues that hinder the segmentation accuracy of these curves, particularly in ...
Victor Sanchez +5 more
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WAILS: Watershed Algorithm With Image-Level Supervision for Weakly Supervised Semantic Segmentation
IEEE Access, 2019 Image semantic segmentation has great development in many fields, and the lack of fully supervised segmentation labels has always been a major problem in the development of image semantic segmentation.
Hongming Zhou +4 more
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Medical Image Segmentation Based on Transformer and HarDNet Structures
IEEE Access, 2023 Medical image segmentation is a crucial way to assist doctors in the accurate diagnosis of diseases. However, the accuracy of medical image segmentation needs further improvement due to the problems of many noisy medical images and the high similarity ...
Tongping Shen, Huanqing Xu
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How interaction methods affect image segmentation: user experience in the task [PDF]
, 2013 Interactive image segmentation is extensively used in photo editing when the aim is to separate a foreground object from its background so that it is available for various applications.
Healy, Graham +12 more
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