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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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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A Large-Scale Synthetic Benchmark Dataset for Non-Cooperative Space Target Perception [PDF]
Scientific DataThe automatic, accurate perception of targets in space is a crucial prerequisite for many on-orbit aerospace missions. Therefore, research on perception technologies within spaceborne images is meaningful.
Yuxuan Liu +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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Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI [PDF]
, 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 ...
Baur, Christoph +3 more
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A lightweight network for brain MRI segmentation [PDF]
Scientific ReportsBrain MRI segmentation plays a crucial role in medical imaging, aiding in the identification and monitoring of brain diseases. This research presents a novel deep learning-based framework designed to achieve high segmentation accuracy while maintaining a
Pubali Chatterjee +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.
Ana, Petrovic +2 more
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Scale-space for empty catheter segmentation in PCI fluoroscopic images [PDF]
International Journal of Computer Assisted Radiology and Surgery, 2017 In this article, we present a method for empty guiding catheter segmentation in fluoroscopic X-ray images. The guiding catheter, being a commonly visible landmark, its segmentation is an important and a difficult brick for Percutaneous Coronary Intervention (PCI) procedure modeling.In number of clinical situations, the catheter is empty and appears as ...
Bacchuwar, Ketan +3 more
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MambaMeshSeg-Net: A Large-Scale Urban Mesh Semantic Segmentation Method Using a State Space Model with a Hybrid Scanning Strategy [PDF]
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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