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- W2955411134 abstract "Facial keypoints (FKP) detection is considered as a challenging task in the field of computer vision, as facial features vary from individual to individual. It becomes a more challenging proposition as the same person facial image may also vary due to change in position, size, pose, expression etc. Some methods exist in literature for detection of FKPs. In this paper, a deep architecture is used to locate the keypoints on gray-scale images. As baseline method one hidden layer neural network and convolutional neural networks are built in the proposed work. Additionally, a block of pretrained Inception module is used to extract the intermediate features. Specifically, the sparse structure of Inception model reduces the computational cost of the proposed method significantly. The methods are evaluated on standard dataset and compared with existing state-of-the-art CNN based methods. The obtained results are promising and also bring out the efficiency of the proposed work." @default.
- W2955411134 created "2019-07-12" @default.
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- W2955411134 date "2019-01-01" @default.
- W2955411134 modified "2023-09-23" @default.
- W2955411134 title "Deep Convolutional Neural Network Based Facial Keypoints Detection" @default.
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- W2955411134 doi "https://doi.org/10.1007/978-981-13-8578-0_4" @default.
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