Intelligent Detection System Of Empty Seats In Classroom Based On Deep Learning

Classroom is the main place for college students to study by themselves after class.At present,there is a general shortage of classroom resources in many colleges and universities.Therefore,it has become a research hotspot to help students find the empty seats in the classroom.The core of the research is to detect and identify the empty seats in real time and accurately.In order to solve the problem of college students looking for the self-study classroom and the utilization of college classroom resources,this paper adopts the deep learning target detection algorithm to count the number of college classroom,designs an intelligent detection system of classroom empty seats,which helps college students to find the distribution of classroom empty seats and improve the utilization rate of College self-study classroom.The flow of classroom empty seat intelligent detection system is as follows:firstly,preprocess the collected classroom video image,including light compensation of color balance,histogram equalization,automatic correction of classroom seat area.The processing of classroom image dataset improves the quality of camera imaging and the disadvantages of perspective imaging,and obtains the area of interest to be detected in the classroom seat area.Then,the head is detected by the detection algorithm based on deep learning.In order to reduce the parameters of the model and the hardware burden of the computer,the depth separable convolution is used to reduce the parameters of the model so as to construct the lightweight depth convolution neural network model.The idea of residual network is used to solve the problem of model degradation in the training process.Finally,according to the shape characteristics of the head,the number of people is counted,and finally the distribution of empty seats in the classroom is obtained.The system can effectively detect the specific distribution of empty seats in the current classroom.In the actual scene of classroom empty seat intelligent detection has achieved good results,and finally based on the detection algorithm,designed and developed a convenient wechat program for students to use.The experimental results show that:in different periods of time and different classrooms,the average positive inspection rate of the classroom is higher,and the measured distribution of empty seats in the classroom is compared with the actual situation of empty seats in the classroom,the two are basically the same,which shows that the target detection algorithm based on deep learning is feasible for the detection of students.