Bibliographic citations
Hospinal, O., Jayo, G. (2023). Desarrollo y validación conceptual de modelos de reconocimiento de las especies usando deep learning [Trabajo de investigaciòn, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/667866
Hospinal, O., Jayo, G. Desarrollo y validación conceptual de modelos de reconocimiento de las especies usando deep learning [Trabajo de investigaciòn]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/667866
@misc{renati/1294193,
title = "Desarrollo y validación conceptual de modelos de reconocimiento de las especies usando deep learning",
author = "Jayo Escalante, Geraldine Indira",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
Image recognition is an important task in the field of computer vision and by many researchers in recent years. With the emergence of deep learning, a breakthrough has been achieved in the development of image recognition models. The development and conceptual validation of image recognition models are important to ensure their effectiveness for the specific task for which they were designed. In development, system requirements are defined, relevant features are selected, and the appropriate architecture for the model is determined. Conceptual validation involves evaluation of the models with test data and comparison with other existing models in the field. In conclusion, development and conceptual validation are essential in the process of creating image recognition models. The combination of deep learning and specific image preprocessing techniques have enabled a breakthrough in this area and have proven to be very effective in the image recognition task. However, it is important to keep in mind the importance of an adequate data set for the success of the model.
This item is licensed under a Creative Commons License