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- W4281715358 abstract "The research in the field of automatic face recognition, regarding any questions about the appearance and the location of the static and dynamic characteristics of the disturbance, or brown spots on the face. The results of using MATLAB classification tools. We took a train to a dataset of six words in the faces of the people and for the purposes of the train data set, we have a shared vision of border, pattern, and 90% and 30% of the mask border and pattern for the purpose of the test data set, and we make full use of the FIRST Invariant of the properties and to the structure for the analysis of the patient's symptoms, and then to rank with the help of a Proposed Balanced KNN method to observed maximum accuracy at 95.25%.These are shows result and analysis section shows compressive method result and image analysis results." @default.
- W4281715358 created "2022-06-13" @default.
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- W4281715358 creator A5078399857 @default.
- W4281715358 date "2022-04-21" @default.
- W4281715358 modified "2023-09-30" @default.
- W4281715358 title "Human facial expressions recognition using artificial intelligence K-Nearest Neighbor (KNN) Algorithm" @default.
- W4281715358 doi "https://doi.org/10.1109/icdcs54290.2022.9780832" @default.
- W4281715358 hasPublicationYear "2022" @default.
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