A Deep Learning Model for Chilean Bills Classification
This work addresses a domain-specific problem for automated bill detection and counting, but it is incremental as it applies existing deep learning methods to a new dataset.
The authors tackled the problem of automatically classifying Chilean banknotes using a deep learning model, achieving positive results with data augmentation to address limited image samples.
Automatic bill classification is an attractive task with many potential applications such as automated detection and counting in images or videos. To address this purpose we present a Deep Learning Model to classify Chilean Banknotes, because of its successful results in image processing applications. For optimal performance of the proposed model, data augmentation techniques are introduced due to the limited number of image samples. Positive results were achieved in this work, verifying that it could be a stating point to be extended to more complex applications.