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• W4387403341 endingPage "01082" @default.
• W4387403341 startingPage "01082" @default.
• W4387403341 abstract "To make machines more human-like, computer vision is essential. Computer vision is a field that focuses on mimicking the capabilities of the human visual framework to capture high-level understanding from enhanced images or recordings. Such a computer vision application gives the machine the ability to recognize a person and detect their emotions in order to process them appropriately. Facial verification can be a process of identifying or validating an object through an image, video, or any audio-visual component of their face. It could be a biometric discriminant proof strategy that works directly and confronts measures of discriminating individuals through their facial design and biometric information. The innovation collects a unique set of biometric information from each individual regarding their face and facial expressions to identify an individual. Facial sensory recognition can be an innovation used to analyse estimates from a variety of sources, such as images and recordings. It makes a difference as machines get better the way humans do and treat them according to their emotions. We are using a deep learning computation called Convolutional Neural Networks (CNN) to prepare for this demonstration that determines the sentiment of certain input images. We need to pre-process the images to prepare and test the model. For pre-processing, we do image enhancement combining resizing, equalizing and converting the image to grayscale for the machine to achieve. This demonstration can have multiple applications in both surveillance and feedback systems." @default.
• W4387403341 created "2023-10-07" @default.
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• W4387403341 date "2023-01-01" @default.
• W4387403341 modified "2023-10-07" @default.
• W4387403341 title "Sustainable Facial Authentication and Expression Prediction using Deep Learning Techniques" @default.
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• W4387403341 doi "https://doi.org/10.1051/e3sconf/202343001082" @default.
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