EAR DISEASE DETECTION BY OTOSCOPIC IMAGES USING MATLAB

The diagnosis and classification of ear diseases play a pivotal role in the early detection and effective treatment of various auditory disorders. In this project, we propose a machine learning-based model and ADAM optimization algorithm approach for the automated detection and classification of ear diseases using otoscopic images. The focus of our investigation lies in the classification of ear diseases based on tympanic membrane conditions, encompassing a range of conditions with normal ear and acute otitis media, chronic otitis, ear ventilation issues, earwax accumulation, otitis externa, pseudo membrane presence, and tympanosclerosis.