scholarly journals A Method Of Skin Disease Detection Using Image Processing And Machine Learning

2019 ◽  
Vol 163 ◽  
pp. 85-92 ◽  
Author(s):  
Nawal Soliman ALKolifi ALEnezi
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Skin Disease ◽  
Disease Detection

scholarly journals Skin disease detection using Image Processing and Machine Learning

IJARCCE ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 293-297
Author(s):  
Miss. Gauri Khandagale ◽  
Miss. Tejaswini Agunde ◽  
Prof.S.R. Hiray
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Skin Disease ◽  
Disease Detection

scholarly journals A Review of Skin Disease Classification Techniques based on Machine Learning

2021 ◽  
Vol 9 (8) ◽  
pp. 1097-1101
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Skin Cancer ◽  
Basal Cell Carcinoma ◽  
Actinic Keratosis ◽  
Skin Disease ◽  
Skin Diseases ◽  
Skin Condition ◽  
Disease Classification ◽  
Vascular Lesions

Dermatology is one of the most unpredictable and difficult field to diagnose. In this field, more tests are needed to be carried out so as to decide the skin condition the patient may be facing. The time to diagnose may vary according to the different dermatologist. Machine learning and image processing can be used to efficiently detect the skin diseases. There are seven different categories of skin cancer- melanocytic nevi, melanoma, benign keratosis, Basal cell carcinoma, actinic keratosis, vascular lesions and dermatofibroma. The purpose of this review is to outline types, diagnosis, methodology and treatment of skin cancer.

scholarly journals Review and Further Prospects of Plant Disease Detection Using Machine Learning

2021 ◽  
pp. 105-115
Author(s):  
Vempati Ramsanthosh ◽  
Anati Sai Laxmi ◽  
Chepuri Sai Abhinay ◽  
Vadepally Santosh ◽  
Vybhav Kothareddy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Sustainable Development ◽  
Feature Extraction ◽  
Processing Time ◽  
Plant Disease ◽  
Health Surveillance ◽  
Plant Diseases ◽  
Disease Detection ◽  
Machine Learning Methods

Identifying of the plant diseases is essential in prevention of yield and volume losses in agriculture Product. Studies of plant diseases mean studies of visually observable patterns on the plant. Health surveillance and detecting diseases in plants is essential for sustainable development agriculture. It is very difficult to monitor plant diseases manually. It requires a lot of experiences in work, expertise in these field plant diseases and also requires excessive processing time. Therefore; image processing is used to detect plant diseases. Disease detection includes steps such as acquisition, image Pre-processing, image segmentation, feature extraction and Classification. We describe these methods for the detection of plant diseases on the basis of their leaf images; automatic detection of plant disease is done by the image processing and machine learning. The different leaf images of plant disease are collected and feature extracted of the various machine learning methods.

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