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- W4321636081 abstract "Acne has become a common problem in the daily lives of most suffering from skin disorders. It can be classified into three types such as inflammatory, non-inflammatory, and a mixture of both inflammatory and non-inflammatory lesions. Studies show that it can persist in a majority of women younger than 30 and a good number of women under 50. Women contribute two-thirds of the total visits made to a dermatologist throughout the year. Acne has been the most common skin disorder. Hence, it becomes extremely important to design a system that can accurately detect and classify the acne regions on one's face. In this paper, we will be taking stock of various acne detection methods involving traditional and improved algorithms on various datasets. We will also be reviewing some of the image preprocessing techniques to separate and extract the acne lesion more efficiently." @default.
- W4321636081 created "2023-02-24" @default.
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- W4321636081 date "2022-12-02" @default.
- W4321636081 modified "2023-09-26" @default.
- W4321636081 title "A Review on Acne Detection Techniques" @default.
- W4321636081 doi "https://doi.org/10.1109/icast55766.2022.10039536" @default.
- W4321636081 hasPublicationYear "2022" @default.
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