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Superpixel segmentation: A benchmark
Signal Processing: Image Communication, 2017Abstract Various superpixel approaches have been published recently. These algorithms are assessed using different evaluation metrics and datasets resulting in discrepancy in algorithm comparison. This calls for a benchmark to compare the state-of-the-arts methods and evaluate their pros and cons.
Murong Wang +4 more
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International Journal of Remote Sensing, 2023
Convolution in convolutional neural network(CNN) essentially uses a filter (kernel) with shared parameters to achieve feature extraction by computing the weighted sum of the centre pixel and adjacent pixels.
Shike Liang, Zhen Hua, Jin-Jiang Li
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Convolution in convolutional neural network(CNN) essentially uses a filter (kernel) with shared parameters to achieve feature extraction by computing the weighted sum of the centre pixel and adjacent pixels.
Shike Liang, Zhen Hua, Jin-Jiang Li
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Weighted superpixel segmentation
The Visual Computer, 2019Image boundaries and regularity are two important factors in superpixel segmentation. Balancing the influence of image boundaries and regularity is key to producing superpixels. In this paper, we present a novel superpixel segmentation algorithm, called weighted superpixel segmentation (WSS), which is capable of generating superpixels with high ...
Xin Qian +2 more
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Spherical Superpixel Segmentation
IEEE Transactions on Multimedia, 2018These days, superpixel algorithms are widely used in computer vision and multimedia applications. However, existing algorithms are designed for planar images, which are less suited to deal with wide angle images. In this paper, we present a superpixel segmentation method for $\text{360}^\circ$ spherical images.
Qiang Zhao 0005 +5 more
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SLIC Superpixel Segmentation for Polarimetric SAR Images
IEEE Transactions on Geoscience and Remote Sensing, 2022Superpixel segmentation approaches for polarimetric synthetic aperture radar (SAR) images have only been studied in recent years. Simple linear iterative clustering (SLIC) is a simple and efficient superpixel segmentation method, first proposed for ...
Jun-Jun Yin +5 more
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Differential Evolutionary Superpixel Segmentation
IEEE Transactions on Image Processing, 2018Superpixel segmentation has been of increasing importance in many computer vision applications recently. To handle the problem, most state-of-the-art algorithms either adopt a local color variance model or a local optimization algorithm. This paper develops a new approach, named differential evolutionary superpixels, which is able to optimize the ...
Yue-Jiao Gong, Yicong Zhou
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Advanced Engineering Informatics, 2021
The operation of water supply channels is threatened by the occasionally occurred slope damages. Timely detection of their occurrence is critical for the rapid enforcement of mitigation measures. However, current practices based on routine inspection and
Jun-Jie Chen, Dong-Hai Liu
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The operation of water supply channels is threatened by the occasionally occurred slope damages. Timely detection of their occurrence is critical for the rapid enforcement of mitigation measures. However, current practices based on routine inspection and
Jun-Jie Chen, Dong-Hai Liu
semanticscholar +1 more source
Minimum barrier superpixel segmentation
Image and Vision Computing, 2018Abstract Superpixel has become an essential processing unit in many computer vision systems, and superpixel segmentation of images is one of the most important step. In this paper, an efficient superpixel segmentation algorithm was proposed. We introduce a new compact-aware minimum barrier distance for superpixel segmentation (MBS), and a propagation
Yinlin Hu +4 more
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IEEE Transactions on Evolutionary Computation
Feature selection (FS) is a very important technique for hyperspectral image (HSI) classification, as successfully selecting informative features can significantly increase the learning performance while reducing the computational cost.
Lingjie Li +5 more
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Feature selection (FS) is a very important technique for hyperspectral image (HSI) classification, as successfully selecting informative features can significantly increase the learning performance while reducing the computational cost.
Lingjie Li +5 more
semanticscholar +1 more source
Entropy rate superpixel segmentation
CVPR 2011, 2011We propose a new objective function for superpixel segmentation. This objective function consists of two components: entropy rate of a random walk on a graph and a balancing term. The entropy rate favors formation of compact and homogeneous clusters, while the balancing function encourages clusters with similar sizes.
Ming-Yu Liu 0001 +3 more
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