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Vanitha, N.
- A Study on Deep Learning Methods for Skin Disease Classification
Abstract Views :83 |
PDF Views:0
Authors
N. Vanitha
1,
M. Geetha
1
Affiliations
1 Department of Information Technology, Dr.N.G. P Arts and Science College Coimbatore, India, IN
1 Department of Information Technology, Dr.N.G. P Arts and Science College Coimbatore, India, IN
Source
Digital Image Processing, Vol 13, No 1 (2021), Pagination: 6-9Abstract
Dermatological disorders are one among the foremost widespread diseases within the world. Despite being common its diagnosis is extremely difficult due to its complexities of skin tone, color, presence of hair. This paper provides an approach to use various computer vision-based techniques (deep learning) to automatically predict the varied sorts of skin diseases. The system makes use of deep learning technology to coach itself with the varied skin images. the most objective of this technique is to realize maximum accuracy of disease of the skin prediction. The people health quite the other diseases. Skin diseases are mostly caused by mycosis, bacteria, allergy, or viruses, etc. The lasers advancement and Photonics based medical technology is employed in diagnosis of the skin diseases quickly and accurately. The medical equipment for such diagnosis is restricted and costliest. So, Deep learning techniques helps in detection of disease of the skin at an initial stage. The feature extraction plays a key role in classification of skin diseases. The usage of Deep Learning algorithms has reduced the necessity for human labor, like manual feature extraction and data reconstruction for classification purposeKeywords
Disease of the Skin, Deep Learning, Types, Significance.
References
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- Analysis of Machine Learning Techniques for Breast Cancer Prediction
Abstract Views :90 |
PDF Views:0
Authors
N. Vanitha
1,
R. Srimathi
1
Affiliations
1 Department of Information Technology, N.G.P Arts and Science College Coimbatore, IN
1 Department of Information Technology, N.G.P Arts and Science College Coimbatore, IN
Source
Digital Image Processing, Vol 13, No 1 (2021), Pagination: 10-14Abstract
The most frequently happening cancer among Indian women is breast cancer, which is the second most exposed cancer in the world. Here is a chance of fifty percent for fatality in a case as one of two women diagnosed with breast cancer die in the cases of Indian women. With the rapid population growth, the risk of death incurred by breast cancer is rising exponentially. [2] Breast cancer is the second most severe cancer among all of the cancers already unveiled. A machine learning technique discovers illness which helps clinical staffs in sickness analysis and offers dependable, powerful, and quick reaction just as diminishes the danger of death. In this paper, we look at five administered AI methods named Support Vector Machine (SVM), K-closest neighbours, irregular woodlands, fake/artificial neural organizations (ANNs). The performance of the study is measured with respect to accuracy, sensitivity, specificity, precision, negative predictive value. Furthermore, these strategies were evaluated on exactness review region under bend and beneficiary working trademark bend. At last in this paper we analysed some of different papers to find how they are predicted and what are all the techniques they were used and finally we study the complete research of machine learning techniques for breast cancer.Keywords
Breast Cancer, Prediction, Machine Learning.References
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