Results 51 to 60 of about 9,139 (221)
Remote Sensing, 2020 In this paper, superpixel features and extended multi-attribute profiles (EMAPs) are embedded in a multiple kernel learning framework to simultaneously exploit the local and multiscale information in both spatial and spectral dimensions for hyperspectral
Lei Pan, Chengxun He, Yang Xiang, Le Sun
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Remote Sensing, 2022 The discrepancies in existing land cover data are relatively high, indicating low local precision and application limitations. Multisource data fusion is an effective way to solve this problem; however, the fusion procedure often requires resampling to ...
Qi Jin, Erqi Xu, Xuqing Zhang
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Remote Sensing, 2018 Superpixels, as a state-of-the-art segmentation paradigm, have recently been widely used in computer vision and pattern recognition. Despite the effectiveness of these algorithms, there are still many limitations and challenges dealing with Very High ...
Zeinab Gharibbafghi +2 more
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Superpixels and Polygons Using Simple Non-iterative Clustering
Computer Vision and Pattern Recognition, 2017 We present an improved version of the Simple Linear Iterative Clustering (SLIC) superpixel segmentation. Unlike SLIC, our algorithm is non-iterative, enforces connectivity from the start, requires lesser memory, and is faster.
R. Achanta, S. Süsstrunk
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Adaptive Fuzzy Learning Superpixels Representation for PolSAR Image Classification
IEEE Transactions on Geoscience and Remote Sensing, 2021 The increasing applications of Polarimetric SAR (PolSAR) image classification demand for effective superpixels algorithms. Fuzzy superpixels algorithms reduce the misclassification rate by dividing pixels into superpixels, which are groups of pixels of ...
Yuwei Guo +6 more
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Superpixels, Occlusion and Stereo [PDF]
2011 International Conference on Digital Image Computing: Techniques and Applications, 2011 Graph-based energy minimization is now the state of the art in stereo matching methods. In spite of its outstanding performance, few efforts have been made to enhance its capability of occlusion handling. We propose an occlusion constraint, an iterative optimization strategy and a mechanism that proceeds on both the digital pixel level and the super ...
Yuhang Zhang 0001 +3 more
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IEEE Transactions on Image Processing, 2020 Superpixel segmentation is a fundamental computer vision technique that finds application in a multitude of high level computer vision tasks. Most state-of-the-art superpixel segmentation methods are unsupervised in nature and thus cannot fully utilize frequently occurring texture patterns or incorporate multiscale context.
Utkarsh Gaur, B. S. Manjunath
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Research on Dynamic Graph Target Tracking Method Fusing the Color Local Entropy
ITM Web of Conferences, 2018 Focusing on the problems of target deformation, occlusion, background interference and rotation, a robust video tracking method is proposed in this paper, which is based on the superpixels and dynamic graph matching. Firstly, to make the superpixels edge
Zhang Junchang +3 more
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A Survey of Weakly-supervised Image Semantic Segmentation Based on Image-level Labels
Taiyuan Ligong Daxue xuebao, 2021 According to the different ways of image-level label location inference, the weakly-supervised image semantic segmentation methods with image-level labels were divided into superpixel-based methods and classification-network-prior based methods.
Xinlin XIE +5 more
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Multiobjective Evolutionary Superpixel Segmentation for PolSAR Image Classification
Remote SensingSuperpixel segmentation has been widely used in the field of computer vision. The generations of PolSAR superpixels have also been widely studied for their feasibility and high efficiency.
Boce Chu +7 more
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