Preprint Brief Report Version 2 This version is not peer-reviewed

Pattern Recognition with Convolutional Neural Networks: Humpback Whale Tails

Version 1 : Received: 26 February 2019 / Approved: 27 February 2019 / Online: 27 February 2019 (12:14:05 CET)
Version 2 : Received: 12 March 2019 / Approved: 12 March 2019 / Online: 12 March 2019 (10:18:12 CET)

How to cite: De Mingo Lopez, L.F.; Morales Lucas, C.; GOMEZ BLAS, N.; Ivanova, K. Pattern Recognition with Convolutional Neural Networks: Humpback Whale Tails. Preprints 2019, 2019020257 (doi: 10.20944/preprints201902.0257.v2). De Mingo Lopez, L.F.; Morales Lucas, C.; GOMEZ BLAS, N.; Ivanova, K. Pattern Recognition with Convolutional Neural Networks: Humpback Whale Tails. Preprints 2019, 2019020257 (doi: 10.20944/preprints201902.0257.v2).

Abstract

This paper presents a study and implementation of a convolutional neural network to identify and recognize humpback whale specimens from the unique patterns of their tails. Starting from a dataset composed of images of whale tails, all the phases of the process of creation and training of a neural network are detailed – from the analysis and pre-processing of images to the elaboration of predictions, using TensorFlow and Keras frameworks. Other possible alternatives are also explained when it comes to tackling this problem and the complications that have arisen during the process of developing this paper.

Subject Areas

convolutional neural networks; pattern recognition; machine learning

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