In the realm of computer vision, semantic segmentation is the task of recognizing objects in
images at the pixel level. This is done by performing a classification of each pixel. The task is …

In this work we present a large-scale comparison of 21 learning and aggregation methods
proposed in the ensemble learning, social choice theory (SCT), information fusion and …

This paper presents a study on an automated system for image classification, which is based
on the fusion of various deep learning methods. The study explores how to create an …

In this article, we propose a novel probabilistic framework to improve the accuracy of a
weighted majority voting algorithm. In order to assign higher weights to the classifiers which …

Constraining the actions of AI systems is one promising way to ensure that these systems
behave in a way that is morally acceptable to humans. But constraints alone come with …

Interactive image segmentation is a method for precisely segmenting of the object from
background using information entered by the user. However, most interactive segmentation …

In computer vision and image analysis, Convolutional Neural Networks (CNNs) and other
deep-learning models are at the forefront of research and development. These advanced …

Semantic segmentation consists in classifying each pixel of an image by assigning it to a
specific label chosen from a set of all the available ones. During the last few years, a lot of …

For robust classification, selecting a proper classifier is of primary importance. However,
selecting the best classifiers depends on the problem, as some classifiers work better at …

In this work, we present SenTag, a lightweight web-based tool focused on semantic
annotation of textual documents. The platform allows multiple users to work on a corpus of …