Results 1 to 10 of about 8,973,058 (218)
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI [PDF]
Lecture Notes in Computer Science, 2020 Brain pathologies can vary greatly in size and shape, ranging from few pixels (i.e. MS lesions) to large, space-occupying tumors. Recently proposed Autoencoder-based methods for unsupervised anomaly segmentation in brain MRI have shown promising performance, but face difficulties in modeling distributions with high fidelity, which is crucial for ...
Benedikt Wiestler +2 more
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Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods [PDF]
Remote Sensing, 2016 Object-based change detection (OBCD) has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data.
Lei Ma +7 more
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Multiresolution segmentation of natural images: from linear to nonlinear scale-space representations [PDF]
IEEE Transactions on Image Processing, 2004 In this paper, we introduce a framework that merges classical ideas borrowed from scale-space and multiresolution segmentation with nonlinear partial differential equations. A non-linear scale-space stack is constructed by means of an appropriate diffusion equation.
P Vandergheynst
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HiMamba-Net: a Hilbert-serialized Mamba network for 3D point cloud instance segmentation [PDF]
Scientific ReportsInstance-level segmentation of large-scale 3D point clouds is a fundamental yet challenging task due to complex spatial structures, severe occlusions, and long-range dependencies.
Kai Zhao +4 more
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IEEE AccessMedical image segmentation plays an essential role in computer-aided diagnosis, supports physicians with fast and accurate information to make timely treatment decisions.
Yu Liu, Yanping Chen, Yang Yu
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Image segmentation through the scale-space random walker [PDF]
, 2021 This thesis proposes an extension to the Random Walks assisted segmentation algorithm that allows it to operate on a scale-space. Scale-space is a multi-resolution signal analysis method that retains all of the structures in an image through progressive blurring with a Gaussian kernel.
Richard Rzeszutek
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Remote SensingSemantic segmentation of urban meshes plays an increasingly crucial role in the analysis and understanding of 3D environments. Most existing large-scale urban mesh semantic segmentation methods focus on integrating multi-scale local features but struggle
Wenjie Zi +3 more
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A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses.
A. Hadavand +2 more
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Scale Space Operators on Hierarchies of Segmentations [PDF]
, 2013 A hierarchy of segmentations(partitions) is a multiscale set representation of the image. This paper introduces a new set of scale space operators or transformations on the space of hierarchies of partitions. An ordering of hierarchies is proposed which is endowed by an ω-ordering based on a global energy over the classes of the hierarchy.
Bangalore Ravi Kiran, Jean Serra
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Coarse-to-Fine Segmentation With Shape-Tailored Scale Spaces [PDF]
CoRR, 2016 We formulate a general energy and method for segmentation that is designed to have preference for segmenting the coarse structure over the fine structure of the data, without smoothing across boundaries of regions. The energy is formulated by considering data terms at a continuum of scales from the scale space computed from the Heat Equation within ...
Ganesh Sundaramoorthi +2 more
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