Machine learning in classification of latex gloves
Abstract: The project consists in develop a tool that make a classification of latex gloves taking into account the different features that make the difference between them using a Matlab code in machine learning. This project has the purpose to have a tool that classify those gloves in order to know in which market of the world they could be sold and at what price. So as to achieve this purpose, it is necessary to collect the data and prepare them to introduce in the code. The project can be divided in three different parts; the first one is to make a research of all the theory about latex gloves, achieve the basic fundamentals with the program Matlab and the theory about image processing and machine learning. After that, I will collect the 125 data and the features to take into account are if the gloves have black spots and if they are yellow or white colour. With all the material, it will possible to generate a code in Matlab to prepare all the data and finally, train a model with machine learning. After training this model, the classifier performed well, achieving 82% accuracy. However, it is not perfect because the main mistake has been in the images taken, some of the gloves had wrinkles, so the code detects them as black spots. That is why, as a future work, the quality of the images should be improved in order to not have wrinkles and hence improve the precision for the classifiers. Moreover, it has been proven that this tool can be implemented in the company that has provided the gloves. With that, his plan to sell gloves in Europe could be feasible if the bath of gloves accomplishes the required Acceptance Quality Limit but it has not been possible to prove because the gloves have not been randomly selected to carry out this project. Even so knowing that the code works, it could be applied to corroborate this fact.
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