Results 1 to 10 of about 89,812 (160)
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI [PDF]
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 ...
Christoph Baur +2 more
exaly +3 more sources
LTM-UNet: Linear Transformer–Mamba with Attention-Based U-Net for Context-Aware Breast Ultrasound Image Segmentation [PDF]
Background/Objectives: Accurate breast lesion segmentation using deep learning models requires precise understanding of both global contextual relevance and finer lesion structure details, which remains a challenge for existing convolutional and ...
Shivpratap Singh Kushwah +3 more
doaj +2 more sources
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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SADNet: Space-aware DeepLab network for Urban-Scale point clouds semantic segmentation
Semantic 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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Image Semantic Segmentation Based on Multi-level Superposition and Attention Mechanism [PDF]
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
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
doaj +1 more source
Multi-Scale Deep Neural Network Based on Dilated Convolution for Spacecraft Image Segmentation
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
doaj +1 more source
Colour Morphological Scale-Spaces for Image Segmentation [PDF]
Morphological scale-spaces have become an important tool for analysing greyscale images. However, their extension to colour images has proven elusive until recently. In this paper an original evaluation of two recently proposed colour sieves is presented, both algorithmically and in terms of their computational and segmentation performance.
David Gimenez, Adrian N. Evans
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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
doaj +1 more source
Scale Space Operators on Hierarchies of Segmentations [PDF]
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.
Kiran, Bangalore Ravi, Serra, Jean
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