An automatic mechanism for the selection of image subset of modern and historic images out of a landmark large image set collected from the internet is designed in this paper. This selection depends on the extraction of dominant features using Gabor filtering. These features are selected carefully from a preliminary image set and fed into a neural network as a training set. The mechanism collec...

As an important upstream task for many medical applications, supervised landmark localization still requires non-negligible annotation costs to achieve desirable performance. Besides, due cumbersome collection procedures, the limited size of datasets impacts effectiveness large-scale self-supervised pre-training methods. To address these challenges, we propose a two-stage framework one-shot loc...