Multimodal Group Activity State Detection for Classroom Response System Using Convolutional Neural Networks

Sebastian, Abraham Gerard; Singh, Shreya; Manikanta, P.; Ashwin, T. S.; Reddy, G. Ram Mohana

doi:10.1007/978-981-10-8639-7_25

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2019

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“…CONVOLUTIONAL LAYERS Convolution layers generate feature maps that represent how pixel values are enhanced, for example, edge and pattern detection. A feature map is formed by applying filter one transversely the entire image [4]. Pooling is a dimension reduction technique, which is usually applied after one or several convolutional layers when building CNN's as adding more convolutional layers can significantly affect computational time.…”

Section: IVmentioning

confidence: 99%

Emotion Detection and Performance Prediction of Student using CNN

Kumar¹

2019

IJRASET

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Artificial intelligence is making a new world with the most advanced technology like machine learning, deep learning, computer vision and Robotics process automation. The techniques are making human to reduce their physical efforts, save times and accuracy more than human where human can't perform those task. With human effortless, as lots of research are done in this filed, its uses of application are also developed like self-driving card, face recognition, emotion recognition, speech recognition and many more. In this research, we are implemented a smart classroom technique using computer vision and emotion recognition for multiple faces of student and detect different types of emotion during lecture and plot a final result to predict their performance in the upcoming exam.

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Section: IVmentioning

confidence: 99%

Emotion Detection and Performance Prediction of Student using CNN

Kumar¹

2019

IJRASET

View full text Add to dashboard Cite

show abstract

Multimodal Group Activity State Detection for Classroom Response System Using Convolutional Neural Networks

Cited by 1 publication

References 3 publications

Emotion Detection and Performance Prediction of Student using CNN

Emotion Detection and Performance Prediction of Student using CNN

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