Authors :
Ashlesha Gaikwad; Meghna Sonayallu; Shivani Tilekar; A.S.Deokar
Volume/Issue :
Volume 5 - 2020, Issue 6 - June
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/38RZYn3
DOI :
10.38124/IJISRT20JUN711
Abstract :
Skin diseases are considered one of the biggest
scientific troubles in 21st century because of its especially
complex and luxurious prognosis with problems and
subjectivity of human interpretation. In cases of deadly
illnesses like Melanoma prognosis in early tiers play a
critical part in determining the possibility of getting
cured. The software of automated strategies will assist in
early diagnosis specifically with photographs with
variety of analysis. Hence, in this system we present a
completely automated machine of skin sickness
recognition via lesion images, a device intervention in
evaluation to traditional clinical personnel based
detection. This system is designed into 3 levels
compromising of statistics series and augmentation,
designing version and subsequently prediction of disease.
This proposed system uses more than one AI algorithms
like Convolutional Neural Network and naive Bayes
classifier and amalgamated it with image processing
tools to shape a higher shape, leading to better accuracy.
Keywords :
Convolutional Neural Network, Naive Bayes classifier, Dermatological Disorders, Machine Learning.
Skin diseases are considered one of the biggest
scientific troubles in 21st century because of its especially
complex and luxurious prognosis with problems and
subjectivity of human interpretation. In cases of deadly
illnesses like Melanoma prognosis in early tiers play a
critical part in determining the possibility of getting
cured. The software of automated strategies will assist in
early diagnosis specifically with photographs with
variety of analysis. Hence, in this system we present a
completely automated machine of skin sickness
recognition via lesion images, a device intervention in
evaluation to traditional clinical personnel based
detection. This system is designed into 3 levels
compromising of statistics series and augmentation,
designing version and subsequently prediction of disease.
This proposed system uses more than one AI algorithms
like Convolutional Neural Network and naive Bayes
classifier and amalgamated it with image processing
tools to shape a higher shape, leading to better accuracy.
Keywords :
Convolutional Neural Network, Naive Bayes classifier, Dermatological Disorders, Machine Learning.
