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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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Coarse-to-Fine Segmentation With Shape-Tailored Scale Spaces [PDF]
, 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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Multi-scale space smoothing and segmentation of range data for robot navigation [PDF]
, 2010 One of the most essential problems for mobile robot navigation is to enable an autonomous robot to navigate in an unknown environment and to incrementally build a map of this environment while simultaneously using this map to compute its current location. This problem is usually referred to as Simultaneous Localization and Mapping (SLAM).
Fan Tang
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SADNet: Space-aware DeepLab network for Urban-Scale point clouds semantic segmentation
International Journal of Applied Earth Observations and GeoinformationSemantic segmentation of urban-scale point clouds can effectively assist people in understanding and perceiving 3D urban scenes. Although a considerable number of deep learning models for the semantic segmentation of point clouds have been proposed, some
Wenxiao Zhan, Jing Chen
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Scale Space Approximation in Convolutional Neural Networks for Retinal Vessel Segmentation [PDF]
, 2018 10 pages, 7 ...
Kyoung Jin Noh +2 more
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Fast Mumford-Shah segmentation using image scale space bases [PDF]
SPIE Proceedings, 2007 Image segmentation using the piecewise smooth variational model proposed by Mumford and Shah is both robust and computationally expensive. Fortunately, both the intermediate segmentations computed in the process of the evolution, and the final segmentation itself have a common structure.
Christopher Alvino, Anthony Yezzi
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Image Semantic Segmentation Based on Multi-level Superposition and Attention Mechanism [PDF]
Jisuanji gongcheng, 2023 To address the common problems such as small-scale targets being easily lost and boundary segmentation being discontinuous owing to the complexity of target space, a semantic image segmentation model based on multi-level superposition and attention ...
Xiaodong SU, Shizhou LI, Jiayuan ZHAO, Hongyu LIANG, Yurong ZHANG, Hongyan XU
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Latent space unsupervised semantic segmentation
Frontiers in Physiology, 2023 The development of compact and energy-efficient wearable sensors has led to an increase in the availability of biosignals. To effectively and efficiently analyze continuously recorded and multidimensional time series at scale, the ability to perform ...
Knut J. Strommen +4 more
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Multi-Scale Deep Neural Network Based on Dilated Convolution for Spacecraft Image Segmentation
Sensors, 2022 In recent years, image segmentation techniques based on deep learning have achieved many applications in remote sensing, medical, and autonomous driving fields.
Yuan Liu +5 more
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IET Image Processing, 2023 Iris segmentation is a critical step in the iris recognition system. Since the quality of iris database taken under different camera sensors varies greatly, thus most existing iris segmentation methods are designed for a particular collection device ...
Guang Huo, Dawei Lin, Meng Yuan
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