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- W3206882128 abstract "This paper intends to develop a novel FER model, which consists of four stages: (1) face detection, (2) feature extraction, (3) dimension reduction, and (4) classification. In this context, the face detection is done using Viola Jones method (VJ). It is the first object recognition model to offer better recognition rates in real-time. Further, features extraction techniques like local binary pattern (LBP) and discrete wavelet transform (DWT) are used for extracting the features from face detected images. Moreover, the dimension reduction of features is done using principal component analysis (PCA), which is an arithmetical process that exploits an orthogonal transformation to exchange a group of annotations of probably interrelated constraints. The classification procedure is performed using neural network (NN), with the new training algorithm called bird swarm algorithm, which is modified based on probability and hence termed as probability-based BSA (P-BSA)." @default.
- W3206882128 created "2021-10-25" @default.
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- W3206882128 date "2021-10-01" @default.
- W3206882128 modified "2023-09-26" @default.
- W3206882128 title "Automatic Face Emotion Recognition With the Aid of Probability-Based Bird Swarm-Trained Neural Network" @default.
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- W3206882128 doi "https://doi.org/10.4018/ijsir.2021100101" @default.
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