• Jageti Padmavathy

With the development of computer technology, accurate and quicker findings may be produced, and patients can be treated as necessary. More people have skin conditions than other illnesses. Skin conditions can be brought on by viruses, germs, allergies, fungal infections, and more. An effective method to pinpoint specific types of skin illnesses has been proposed by a recent study. The development of automated techniques is required to improve the precision of skin disease diagnosis. Therefore, image processing methods aid in the beginning development of automated dermatology screening systems. We suggested a method for identifying skin conditions based on image processing. Check the skin photograph you uploaded for signs of skin illness. This technique uses image analysis to determine the type of disease by taking a digital photograph of the affected skin area. Our suggested method is easy, quick, and doesn't call for pricey equipment. Any device with internet connectivity can use it. For successful identification, accurate skin disease detection and classification are crucial, and image processing with the use of machine learning algorithms can be used to accomplish this.

Convolutional Neural Networks, Artificial Networks, Image Processing, Deep Learning.

"Skin Afflictions Unveiled: Classification of Dermatological Diseases using Convolution Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.f590-f597, November-2024, Available :http://www.jetir.org/papers/JETIR2411568.pdf

"Skin Afflictions Unveiled: Classification of Dermatological Diseases using Convolution Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppf590-f597, November-2024, Available at : http://www.jetir.org/papers/JETIR2411568.pdf