Automatic Classification of Semi Precious Rocks

Irving Alberto Cruz Matías, Constantino Pearl, Andrea Puente

Resultado de la investigación

Resumen

This project pretends to reach a successful model of automatic classification of semi precious rocks through Machine Learning techniques in TensorFlow and OpenCV image processing algorithms. Visual characteristics and image processing algorithms were proposed to correctly seg-ment the objects and identify their key features. After that, different TensorFlow models (DenseNet, NasNet, etc.) were tested to measure their accuracy and select the best method based on a comparative between performance and precision.
The results from the experiments were assessed and the definite algorithm was construct-ed. The algorithm runs on an Amazon Web Services instance, which is accessed by a mobile application. Results, scope and project limitations are discussed at the end of this work, as well as future approaches.
Idioma originalEnglish
EstadoIn preparation - 2019
Evento2020 Winter Conference on Applications of Computer Vision - Snowmass Village, Colorado
Duración: 2 mar 20205 mar 2020
http://wacv20.wacv.net/

Conference

Conference2020 Winter Conference on Applications of Computer Vision
Título abreviadoWACV20
PaísUnited States
CiudadColorado
Período2/3/205/3/20
Dirección de internet

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  • Citar esto

    Cruz Matías, I. A., Pearl, C., & Puente, A. (2019). Automatic Classification of Semi Precious Rocks. Papel presentado en 2020 Winter Conference on Applications of Computer Vision, Colorado, .