Intelligent machines are being used by professionals in the healthcare industry and its usefulness is undoubted. These machines accept data in different forms, like texts or images, and an interpretation or action that helps with the diagnosis or treatment is provided. A similar technology for use by the patient to check for skin diseases can be very beneficial for patients living in countries where healthcare is expensive or inaccessible.
The steps included in image classification are inputting the image data, detecting the image, extracting unique features from the scanned image using a Convolutional Neural Network (CNN). If the feature extracted contains useful information with reference to the dataset, it can be used to predict the image correctly. All the steps and processes needed to solve this image classification problem are documented in this poster.
This research also focuses on the accuracy of the image classification due to the importance of accuracy in the health industry. Hence, the efficiency of the algorithms used would be compared in this poster and evaluated to deduce which is best for classification of image with tiny and repeating details.