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http://hdl.handle.net/10609/132286
Title: | Exploración de Vision Transformer para la clasificación de células normales de sangre periférica |
Author: | Ryba Maciejewska, Belén |
Tutor: | Alférez, Santiago |
Others: | Calvet Liñán, Laura |
Abstract: | Although Convolutional Neuronal Networks have revolutionized the world of computer vision,with the increasing size of datasets and the continuous development of new techniques, these models are beginning to present limitations, especially due to their high processing time. The following work analyzes Vision Transformer, a new proposed architecture that would allow overcoming these restrictions. Focusing its application in the field of computer science for the automatic recognition of cells in peripheral blood. The results obtained, with a higher classification accuracy than 0.96, show that ViT-based models are a promising alternative to the well-known CNN-based models for the performance of this type of tasks. In addition, a simple graphical interface is implemented with the aim of bringing users closer to the use of this type of algorithms for classification tasks, without any deep computer knowledge. |
Keywords: | Visual Transformer deep learning image classification |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2021 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
Files in This Item:
File | Description | Size | Format | |
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brybaTFM0621memoria.pdf | Memoria del TFM | 2,51 MB | Adobe PDF | View/Open |
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