| 000 | 01357nam a2200121Ia 4500 | ||
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| 008 | 231221s9999 xx 000 0 und d | ||
| 041 | _aEnglish | ||
| 100 | _aMeenakshi, M M. | ||
| 245 | 0 |
_aDermatological disease detection using image processing and machine learning _bNatarajan, S. |
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| 260 |
_cJan-May 2019 _bPES University _aBengaluru |
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| 510 | _aDermatological Diseases are one of the biggest medical issues in 21st century due to its highly complex and expensive diagnosis with difficulties and subjectivity of human interpretation. In cases of fatal diseases like Melanoma diagnosis in early stages play a vital role in determining the probability of getting cured. We believe that the application of automated methods will help in early diagnosis especially with the set of images with variety of diagnosis. Hence, in this article we present a completely automated system of dermatological disease recognition through lesion images, a machine intervention in contrast to conventional medical personnelbased detection. Our model is designed into three phases compromising of data collection and augmentation, designing model and finally prediction. We have used multiple AI algorithms like Convolutional Neural Network and Support Vector Machine and amalgamated it with image processing tools to form a better structure, leading to hig | ||
| 942 | _cCD | ||
| 999 |
_c237123 _d237123 |
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