Abstract: Image classification is a computer vision task that has several applications in diverse fields like security, biology or medicine; and, currently, deep learning techniques have become the state-of-the-art to create image classification models. This growing use of deep learning techniques is due to the large amount of data, the fast increase of the computer processing capacity, and the openness of deep learning tools. However, whenever deep learning techniques are used to solve a classification problem, we can find several deep learning frameworks with their own peculiarities, and different models in each framework; hence, it is natural to wonder which option fits better our problem. In this paper, we present DeepCompareJ, an open-source tool that has been designed to compare, with respect to a given dataset, the quality of deep models created using different frameworks.
Publication Year: 2020
Publication Date: 2020-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 1
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