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http://hdl.handle.net/10609/88605
Title: Object recognition in images. A deep learning approach
Author: Rodríguez Olmos, Miguel Andrés
Director: Bosch Rue, Anna
Keywords: computer vision
deep learning
image processing
Issue Date: Jan-2019
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: We employ methods from deep learning for image recognition. We use a dataset with +70k images and 73 classes in order to compare the performance of several well known deep network architectures. The approaches used include the full training of these networks and also the techniques of transfer learning and fine tuning with the weights pretrained on the ImageNet set. We show the superiority of the latter approach in our dataset. We also experiment with a reorganization of the labels in our dataset by grouping several classes shown by the confusion matrix to be indistinguishable for the models. In this case we obtain a classification accuracy score higher than 50%.
Language: English
URI: http://hdl.handle.net/10609/88605
Appears in Collections:Bachelor thesis, research projects, etc.

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