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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.

An ensemble of Deep Convolutional Neural Networks for Marking Hair Follicles on Microscopic Images