Results 31 to 40 of about 9,139 (221)
Semi-automatic segmentation of skin lesions based on superpixels and hybrid texture information
Medical Image Anal., 2022 Dermoscopic images are commonly used in the early diagnosis of skin lesions, and several computational systems have been proposed to analyze them. The segmentation of the lesions is a fundamental step in many of these systems. Therefore, a semi-automatic
E. Santos +6 more
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Heterogeneous Images Change Detection Based on Iterative Joint Global–Local Translation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Most heterogeneous change detection methods based on transfer learning may not yield satisfactory results due to the lack of comprehensive utilization of the global and local characteristics of the image.
Hao Chen, Fachuan He, Jinming Liu
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Self-Adaptive Superpixels Based on Neural Network Models
IEEE Access, 2020 In this paper, the self-adaptive superpixels are generated based on a neural network model. Superpixels are clusters of pixels, which can simplify the expression of images. Superpixels are widely used in the field of video/image processing.
Xiuxiu Bai, Cong Wang, Zhiqiang Tian
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HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2021 Superpixels serve as a powerful preprocessing tool in numerous computer vision tasks. By using superpixel representation, the number of image primitives can be largely reduced by orders of magnitudes. With the rise of deep learning in recent years, a few
Hankui Peng +2 more
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Hybrid superpixel segmentation [PDF]
2015 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2015 Superpixel over-segment image into meaningful clusters so that pixels in each cluster belong to one object. Many state-of-art superpixel algorithms have to make trade-offs between different concerns. As a result, algorithms that can produce good result in some situations fail in another.
Yuan Liu +3 more
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Scale‐adaptive superpixels for medical images
Quantitative Biology, 2022 Background Superpixel segmentation is a powerful preprocessing tool to reduce the complexity of image processing. Traditionally, size uniformity is one of the significant features of superpixels. However, in medical images, in which subjects scale varies
Limin Sun, Dongyang Ma, Yuanfeng Zhou
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Optimized method for segmentation of ancient mural images based on superpixel algorithm
Frontiers in Neuroscience, 2022 High-precision segmentation of ancient mural images is the foundation of their digital virtual restoration. However, the complexity of the color appearance of ancient murals makes it difficult to achieve high-precision segmentation when using traditional
Jinxing Liang +10 more
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Scale-Adaptive Superpixels [PDF]
Color and Imaging Conference, 2018 Size uniformity is one of the prominent features of superpixels. However, size uniformity rarely conforms to the varying content of an image. The chosen size of the superpixels therefore represents a compromise - how to obtain the fewest superpixels without losing too much important detail.
Achanta, Radhakrishna +3 more
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Infrared Image Superpixel Segmentation Based on Seed Strategy of Contour Encoding
Applied Sciences, 2022 Superpixel segmentation has become a crucial pre-processing tool to reduce computation in many computer vision applications. In this paper, a superpixel extraction algorithm based on a seed strategy of contour encoding (SSCE) for infrared images is ...
Weihua Li +3 more
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IEEE Transactions on Image Processing, 2018 Superpixel segmentation is becoming ubiquitous in computer vision. In practice, an object can either be represented by a number of segments in finer levels of detail or included in a surrounding region at coarser levels of detail, and thus a superpixel segmentation hierarchy is useful for applications that require different levels of image segmentation
Xing Wei 0001 +4 more
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