CLASSIFICATION OF WWII TANKS AND VEHICLES IMAGES FROM CONVOLUTIONAL NEURAL NETWORKS

Leonardo Lago; Rodrigo Monteiro de Lima; Allan Cruz; Pamela Cruz

Autores

Leonardo Lago Centro Universitário UNDB
Rodrigo Monteiro de Lima Centro Universitário UNDB
Allan Cruz Universidade Federal do Maranhão
Pamela Cruz Universidade de Coimbra

Palavras-chave:

Neural networks, Classification, Vehicles, Second World War

Resumo

This paper describes an analysis of the application and development of a Convolutional Neural Network (CNN) applied in the binary classification of World War II vehicle images, allowing the evaluation of the applied concepts, project feasibility and results obtained. Using a grayscale image base, with about 122 training images for the CNN and 15 images for validation, it was possible to identify an average hit rate of 86.666% among the tests performed, demonstrating that it is It is possible to use a CNN to classify images of WWII vehicles automatically with an acceptable degree of accuracy.

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