This paper presents an application of a Convolutional Neural Network as a solution for a task associated with ESENSEI Challenge: Marking Hair Follicles on Microscopic Images. As we show in this paper quality of classification results could be improved not only by changing architecture but also by ensemble networks. In this paper, we present two solutions for the task, the first one based on benchmark convolutional neural network, and the second one, an ensemble of VGG-16 networks. Presented models took first and third places in the final competition leaderboard.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.