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- W4387272242 abstract "Feelings play an important role in our daily lives. Humans can sense a person's emotional state. These robots will, nevertheless, be necessary to recognize people's emotions in particular situations. AI is a sort of artificial intelligence that enables robots to conduct errands. Machine learning algorithms may quickly pick up on emotion identification as a fundamental module. This model explains how to recognize happy, angry, sad, disgusted, neutral, and fearful facial emotions. A variety of networks, such as ANN and CNN, are there to prepare photo data, Outer Networks, and other neural networks. In photo processing, deep learning (DL)-based emotion identification outperforms classical approaches. This study demonstrates how an artificial intelligence system that can differ between emotions that are based on facial features has been developed. Detecting face, extracting features, and classifying emotions are the three processes involved in identifying emotions. Two datasets are used to evaluate the proposed method's presentation. Face emotion recognition is a difficult task (FER-2013). Superintendence rule maintainers and managers who control crowds can also benefit from facial noticing. Using face photographs, this paper demonstrates a method for detecting various mood behaviors such as anger, neutrality, fear or anxiety, happiness, sadness, and a surprising feeling." @default.
- W4387272242 created "2023-10-03" @default.
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- W4387272242 date "2023-01-01" @default.
- W4387272242 modified "2023-10-03" @default.
- W4387272242 title "Detection of emotions with deep learning" @default.
- W4387272242 doi "https://doi.org/10.1049/icp.2023.1809" @default.
- W4387272242 hasPublicationYear "2023" @default.
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