RethNet Model: Object-by-Object Learning for Detecting Facial Skin Problemsby@shohbek
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RethNet Model: Object-by-Object Learning for Detecting Facial Skin Problems

by Shohrukh Bekmirzaev4mJanuary 11th, 2020
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In August 2019, a group of researchers from lululab Inc propose the state-of-the-art concept using a semantic segmentation method to detect the most common facial skin problems accurately. The work is accepted to ICCV 2019 Workshop. The concept of Object-by-Object Learning is observed when an object can be identified by looking at other objects. The detection decisions about individual skin lesions can be switched dynamically through contextual relations among object classes. The use of the REthinker modules forces networks to capture the contextual relationships between object classes regardless of similar texture.

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Shohrukh Bekmirzaev

Shohrukh Bekmirzaev

@shohbek

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