Edge Impulse Potential to Enhance Object Recognition Through Machine Learning

Abstract

Machine Learning (ML) is a powerful artificial intelligence branch that can help businesses, whether small or large, in a variety of industries. It is an option for replacing resources with high operating costs. The aim of this study was to use the Edge Impulse platform as an ML tool option. The system applies low-code frameworks which abstracts a series of complex techniques applied in ML, such as data processing and AI components structure. It implies a time reduction during the development period. Using Edge Impulse allows a more user-friendly interface alternative with an easy-to-interpret logic flow. The study focused an application to do an object recognition, aiming the system capacity limit. The autogenerated accuracy value, pointed by the system indicated 97.9 % after the training step and 89 % after retesting the first 20 mices, photographed in different image angles, indicating a possible model overfitting. Even though, the system showed promise in terms of classifying objects. Some adjustments in the image dataset can improve the model capacity of recognition, as the amount of images showed insufficient at the survey's conclusion.