Image Data Classification Using Mobile Net for Big Data Analytics

Deep learning has more advantages than machine learning approaches, with applications including picture classification, image analysis, clinical archives, and beholding. The archives of medical photographs are developing tremendously as a result of hospitals' extensive use of digital images as data. Digital images play an important part in forecasting the severity of a patient's condition, and medical images are widely used in identification and inquiry. Because of recent advancements in imaging technology, identifying medical images in a automatic manner is an open Research Problem for computer vision experts. A best suited most significant for classifying medical images in accordance with their relevant categories. It has been a propensity to provide a model in which an algorithmic program is taught for identifying medical related images using Deep Learning techniques. A pre-trained DCNN Google net and Mobile net are used to classify a variety of medical images for various body parts, and the models are compared. This image categorization technique is useful for predicting the acceptable class or classes of random unfamiliar images. The experiment's results show that proposed method will be best suited to classify a wide range of medical images.