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Student learning emotion recognition method based on convolutional neural network

A technology of convolutional neural network and identification method, which is applied in the direction of neural learning method, biological neural network model, neural architecture, etc., can solve the problems that teachers cannot pay attention in time, and everyone's learning status cannot be supervised, and achieve the effect of solving difficult perception

Pending Publication Date: 2021-11-16
XIAN UNIV OF TECH
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The invention proposes a method for identifying students' learning emotions based on convolutional neural networks, which solves the problem that teachers cannot pay attention to everyone's learning status and cannot supervise students' learning emotions in a timely manner, and provides support for ensuring classroom quality

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  • Student learning emotion recognition method based on convolutional neural network
  • Student learning emotion recognition method based on convolutional neural network
  • Student learning emotion recognition method based on convolutional neural network

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Embodiment Construction

[0071] The specific implementation manner of the present invention will be described below in conjunction with the accompanying drawings.

[0072] Such as figure 1 , the present invention is based on the recognition method of the student learning emotion of convolutional neural network, specifically comprises the following steps:

[0073] Step 1: Collect student video through the camera, and perform frame skip processing on the video, extract an image every 10 frames, and save it as a video sequence, which can not only save the student's image but also reduce the amount of image data.

[0074] Step 2: Use the AdaBoost face detection method based on Haar-like features to detect and locate the face in the video sequence intercepted in step 1, mark the student's face, and obtain the facial area, such as figure 2 As shown in the flow chart of the AdaBoost algorithm, step 2 is specifically:

[0075] Step 2.1, use Haar-like features to describe the face features for the training ...

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Abstract

The invention discloses a student learning emotion recognition method based on a convolutional neural network. The method comprises the following steps: classifying the expressions of a student through a convolutional neural network model, dividing the learning emotion of the student into positive emotion and negative emotion according to the expressions, storing the student information and emotion information, and feeding back the learning emotion of the student to a teacher. Parents and students can solve the problem that emotions of the students are not easy to perceive, support is provided for teachers to optimize classroom settings and pay attention to learning emotions of the students, a positive role is played in guaranteeing the classroom effect, support can be provided for online learning and detection of student input degree, and an educator can adjust teaching strategies and a learner can adjust learning states.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and in particular relates to a method for identifying students' learning emotions based on a convolutional neural network. Background technique [0002] With the maturity and popularization of Internet technology and multimedia technology, online education is booming. With its unique advantages in time and space, online education allows learners to learn high-quality courses at home and abroad more conveniently, and online learning has become the choice of more and more people. However, because teachers and students are isolated by the network, teachers cannot monitor students' learning status in real time, cannot perceive students' learning emotions, and cannot adjust teaching strategies in time, so the learning effect cannot be guaranteed. At the same time, because there is no emotional communication with teachers, students are learning Problems such as fatigue, weariness, and lack of...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/40G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/084G06F18/285G06F18/2431
Inventor 张彤刘娇娇朱磊姬文江王一川金楠
Owner XIAN UNIV OF TECH
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