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Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...
Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power.Simultaneously, a critical pain point arises as several computer vision applications are deployed ...
This paper introduces TACOSS a text-image alignment approach that allows explainable land cover semantic segmentation by directly integrating semantic concepts encoded from texts. TACOSS combines convolutional neural networks for visual feature extraction ...
The Institute of Electrical and Electronics Engineers, Inc2023
We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety.The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...
Semantic segmentation datasets often exhibit two types of imbalance: \textit{class imbalance}, where some classes appear more frequently than others and \textit{size imbalance}, where some objects occupy more pixels than others. This causes traditional eva ...
Data visualization is a recent domain that founds his roots in the eighties, but its history dates back to more ancient times in other representations such as diagrams, drawings, or maps. In particular, data visualization is hard to take advantage of the h ...
Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...
This dataset includes a total of 635 annotated image patches from historical city maps. It is designed for the semantic segmentation of the maps into 5 semantic classes (building blocks, non-built, water, road network, background frame). 330 patches are ta ...
In this work, we present a new semantic segmentation model for historical city maps that surpasses the state of the art in terms of flexibility and performance. Research in automatic map processing is largely focused on homogeneous corpora or even individu ...
Precisely estimating a robot’s pose in a prior, global map is a fundamental capability for mobile robotics, e.g., autonomous driving or exploration in disaster zones. This task, however, remains challenging in unstructured, dynamic environments, where loca ...
