… The main motivation for this work is to automate the construction of similarity measures … to
effectively learn a similarity measure. Such a learned similarity measure could be used for CBR …

… In the computer vision domain, detecting and tracking people constitutes an important area
[1]. Significant approaches exist to detect pedestrians in monocular images [2]. Recently, …

… suppression model [16], – Determining optimal stopping times in nonlinear diffusion-based
image restoration methods using similarity measurements relative to the original data [17], …

… Part similarity exploration. To assist the similarity measurement between the global feature,
we propose to consider the similarity between part features (details) as well. Following [24], …

… while other is a similarity. Learning style algorithms separated in the form of supervised,
unsupervised, and semi-supervised learning aspects [93, 94]. The similarity is used to grouping …

… This spread of open-source implementations also suggest the popularity of some of the
similarity measures. The similarity measures we chose to compare in this paper, while not as …

… occupied an important position in computer vision tasks. … loss function usually measures the
accuracy, similarity, or goodness … , we have focused on three main tasks in computer vision. …

… tures at instance-level based on visual similarity before inducing group alignment via
adversarial training. We show that both similarity-based grouping and adversarial training allows …

… As the revolution of computer vision (CV) with artificial … However, thanks to the rapid
development of computer vision, there … However, SSIM is utilized to measure the similarity …

… -labels by measuring the feature similarity without considering the distribution discrepancy
… era similarity for pseudo-label generation. We decompose the sample similarity computation …