lihua3154's starred repositories
Facial-Recognition-Based-Attendance-System
Facial Recognition Based Attendance System using Python, Tensorflow, Keras, SqlLite3, Tkinter, OpenCV
Adversarial-Face-Attack
Black-Box Adversarial Attack on Public Face Recognition Systems
CompreFace
Leading free and open-source face recognition system
XTakenFace
XTakenFace is Face Recognition system
Face_recognition_based_attendance_system
A python GUI integrated attendance system using face recognition to take attendance.
Attendace_management_system
In this system we can fill attendance by face recognition
Attendance_Management_System_Using_Face_Recognition
Advance Face Recognition Student Attendance System Project in Python OpenCV With Tkinter GUI & Mysql Database
Attendance-Monitoring-Using-Face-Recognition
Authentication is a significant issue in system control in computer-based communication. Human face recognition is an important branch of biometric verification and has been widely used in many applications, such as video monitor system, human-computer interaction, and door control system and network security. This project describes a method for Student’s Attendance System which will integrate with the face recognition technology using deep learning algorithms. The system will recognize the students present in the classroom and provide the list of present students for the lecture. The primary technique used for the face detection is by using python inbuilt packages of OpenCV. Once the model is trained on different kinds of datasets, the project will help in identifying students present for the class. The front end will be based on an android application. The application uses SQLite database for establishing connection between web app and the model. The backend model mainly comprises of a convolutional neural network which extracts features and trains the model in recognizing those features. The inbuilt OpenCV uses haarcascade classifiers in identifying the faces present in the input image. The list of identified will be displayed as the end result.
College_student_auto_attendance_System_with_tkinter
Face detection and recognition and automatic attendance system
AttendanceSystem
基于 Django + (tensorflow)keras/face-recognition 的人脸识别签到系统
Face-Recognition-System-for-Student-Attendance
Effortlessly track student attendance with our reliable Face Recognition System.
Face-Recognition-Attendance-System
Face Recognition Attendance System
Smart-Attendance-System-using-Face-Recognition
Attendance System using face recognition. Fully automated, UI operated. The model was trained using Keras Sequential layers and Softmax function at the output layer. The data is maintained in MongoDB and CSV at the backend. UI is created using Tkinter
Facial-Recognition-Based-Student-Attendance-System
Face recognition-based attendance system is a process of recognizing the faces of the students while taking attendance by using face bio-metrics based on high – definition monitor video and other information technology. In this face recognition project, a computer system will be able to find and recognize human faces quickly and precisely in images or videos that are being captured through a webcam / a surveillance camera.
Automatic-Attendance-System
End-to-end Face Recognition Video Attendance! - OpenCV face extraction, detection & recognition, PyQt4 GUI and SQLite reports
Classroom-Attendance-System-Utilizing-Viola-Jones-for-Face-Detection-and-LBPH-for-Face-Recognition
The face of a human is crucial for conveying identity. Computer scientists, Neuro scientists, and psychologists, all exploits this human feature using image processing techniques for commercial, and law enforcement applications. Likewise, this feature can be invited into classrooms to maintain records of students’ attendance. Con- temporary traditional way of recording attendance involves human intervention and requires cooperation of the students which is hectic and contribute towards waste of class time. An automated real-time classroom attendance system detects students from still image or video frame coming from a digital camera, and marks his/her attendance by recognizing them. The system utilizes Viola–Jones object detection framework which is capable of processing images extremely rapidly with high detec- tion rates. In the next stage, the detected face in the image is recognized using Local Binary Patterns Histogram.