Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Happy, S"'
Face recognition has been widely accepted as a means of identification in applications ranging from border control to security in the banking sector. Surprisingly, while widely accepted, we still lack the understanding of uniqueness or distinctivenes
Externí odkaz:
http://arxiv.org/abs/2102.04965
Although convolutional neural networks have been proven to be an effective tool to generate high quality maps from remote sensing images, their performance significantly deteriorates when there exists a large domain shift between training and test da
Externí odkaz:
http://arxiv.org/abs/2002.05925
Due to the various reasons such as atmospheric effects and differences in acquisition, it is often the case that there exists a large difference between spectral bands of satellite images collected from different geographic locations. The large shift
Externí odkaz:
http://arxiv.org/abs/1907.12859
Publikováno v:
IEEE Geoscience and Remote Sensing Letters, 2018
Dimensionality reduction (DR) methods have attracted extensive attention to provide discriminative information and reduce the computational burden of the hyperspectral image (HSI) classification. However, the DR methods face many challenges due to li
Externí odkaz:
http://arxiv.org/abs/1812.08047
This work proposes an adaptive trace lasso regularized L1-norm based graph cut method for dimensionality reduction of Hyperspectral images, called as `Trace Lasso-L1 Graph Cut' (TL-L1GC). The underlying idea of this method is to generate the optimal
Externí odkaz:
http://arxiv.org/abs/1807.10602
Publikováno v:
IEEE Geoscience and Remote Sensing Letters, Volume-15, Issue-4, Pages-582-586, 27 February 2018
The lack of proper class discrimination among the Hyperspectral (HS) data points poses a potential challenge in HS classification. To address this issue, this paper proposes an optimal geometry-aware transformation for enhancing the classification ac
Externí odkaz:
http://arxiv.org/abs/1807.02682
In this paper, we propose an L1 normalized graph based dimensionality reduction method for Hyperspectral images, called as L1-Scaling Cut (L1-SC). The underlying idea of this method is to generate the optimal projection matrix by retaining the origin
Externí odkaz:
http://arxiv.org/abs/1709.02920
Feature selection has been studied widely in the literature. However, the efficacy of the selection criteria for low sample size applications is neglected in most cases. Most of the existing feature selection criteria are based on the sample similari
Externí odkaz:
http://arxiv.org/abs/1708.02443
Publikováno v:
IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2016
The poor contrast and the overlapping of cervical cell cytoplasm are the major issues in the accurate segmentation of cervical cell cytoplasm. This paper presents an automated unsupervised cytoplasm segmentation approach which can effectively find th
Externí odkaz:
http://arxiv.org/abs/1702.05506
Publikováno v:
IEEE International Conference on Technology for Education, 2013
In the context of education technology, empathic interaction with the user and feedback by the learning system using multiple inputs such as video, voice and text inputs is an important area of research. In this paper, a nonintrusive, standalone mode
Externí odkaz:
http://arxiv.org/abs/1604.00312