COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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None of the above
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Detailed explanation-1: -To recognize people who were not wearing face masks in government workplaces, Balaji et al. (13) utilized a VGG-16 CNN model developed in Keras/TensorFlow and Open-CV to detect people who were not wearing face masks.
Detailed explanation-2: -Every network has a single input layer and a single output layer. The number of neurons in the input layer equals the number of input variables in the data being processed. The number of neurons in the output layer equals the number of outputs associated with each input.
Detailed explanation-3: -The most common approach seems to be to start with a rough guess based on prior experience about networks used on similar problems. This could be your own experience, or second/third-hand experience you have picked up from a training course, blog or research paper.
Detailed explanation-4: -Deep convolutional neural networks (CNN or DCNN) are the type most commonly used to identify patterns in images and video. DCNNs have evolved from traditional artificial neural networks, using a three-dimensional neural pattern inspired by the visual cortex of animals.