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The Active Segmentation Platform for Microscopic Image Classification and Segmentation
Brain Sciences, 2021 Image segmentation still represents an active area of research since no universal solution can be identified. Traditional image segmentation algorithms are problem-specific and limited in scope.
Sumit K. Vohra, Dimiter Prodanov
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Colour Morphological Scale-Spaces for Image Segmentation [PDF]
Procedings of the British Machine Vision Conference 2005, 2005 Morphological scale-spaces have become an important tool for analysing greyscale images. However, their extension to colour images has proven elusive until recently. In this paper an original evaluation of two recently proposed colour sieves is presented, both algorithmically and in terms of their computational and segmentation performance.
D. Gimenez, A. N. Evans
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A rapid detection method for UAV-borne high-resolution SAR image targets [PDF]
Zhihui kongzhi yu fangzhen, 2023 Aiming at the limited space and resources of the UAV platform, the inaccurate target labeling and excessive calculation amount of high-resolution SAR image detection, a rapid detection method for UAV-borne high-resolution SAR image targets is proposed ...
WANG Zhongbao, YIN Kuiying
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HT-Net: A Hybrid Transformer Network for Fundus Vessel Segmentation
Sensors, 2022 Doctors usually diagnose a disease by evaluating the pattern of abnormal blood vessels in the fundus. At present, the segmentation of fundus blood vessels based on deep learning has achieved great success, but it still faces the problems of low accuracy ...
Xiaolong Hu, Liejun Wang, Yongming Li
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IEEE Access, 2019 Due to the space inconsistency between benchmark image and segmentation result in many existing semantic segmentation algorithms for abdominal CT images, an improved model based on the basic framework of DeepLab-v3 is proposed, and Pix2pix network is ...
Kaijian Xia +4 more
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DroTrack: High-speed Drone-based Object Tracking Under Uncertainty
, 2020 We present DroTrack, a high-speed visual single-object tracking framework for drone-captured video sequences. Most of the existing object tracking methods are designed to tackle well-known challenges, such as occlusion and cluttered backgrounds.
Hamdi, Ali, Kim, Du Yong, Salim, Flora
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Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition [PDF]
, 2017 This paper focuses on multi-scale approaches for variational methods and corresponding gradient flows. Recently, for convex regularization functionals such as total variation, new theory and algorithms for nonlinear eigenvalue problems via nonlinear ...
A Chambolle +22 more
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Learning Rigid Image Registration - Utilizing Convolutional Neural Networks for Medical Image Registration [PDF]
, 2018 Many traditional computer vision tasks, such as segmentation, have seen large step-changes in accuracy and/or speed with the application of Convolutional Neural Networks (CNNs).
Goatman, K.A. +2 more
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Hierarchical image simplification and segmentation based on Mumford-Shah-salient level line selection [PDF]
, 2016 Hierarchies, such as the tree of shapes, are popular representations for image simplification and segmentation thanks to their multiscale structures. Selecting meaningful level lines (boundaries of shapes) yields to simplify image while preserving intact
Géraud, Thierry +2 more
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Selected Applications of Scale Spaces in Microscopic Image Analysis
Cybernetics and Information Technologies, 2015 Image segmentation methods can be classified broadly into two classes: intensity-based and geometry-based. Edge detection is the base of many geometry-based segmentation approaches.
Prodanov Dimiter +2 more
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