Human Burn Diagnosis using Machine Learning
Burn area and depth assessment are critical variables for surveying the degree of burns. This paper presents a characterization model for the treatment of burns, utilizing a machine learning approach. The reason for the examination is to improve the component extraction model to recognize the burn.
The main objective of the research is to provide a novel method that can perform better with a state-of-the-art machine learning technique to segment with the SVM on the burn images. The proposed method is freeware using a machine learning approach with SVM (MLSF-SVM). In the training of the framework, we labeled 1000 and 74 images from COCO and BIS data set respectively and trained our model on 1000 images. As a result, the comparison is made on different state of the art methods. Finally, the accuracy of the model is much better using both of the data sets