AI-Powered Face Recognition Attendance System Dataset and Code

his repository contains the complete dataset and implementation code for the research paper titled “An Efficient AI-Powered Face Recognition System Using ResNet-34: A Comparative Evaluation with LBPH, Eigenfaces, and FaceNet Models.” The project implements five face recognition algorithms (LBPH, PCA, FaceNet + SVM, MTCNN + FaceNet, and ResNet-34) for automated classroom attendance using webcam video feed. The dataset includes facial images of participants organized by name. Code scripts include: collect_faces.py: For capturing training images train_model.py, train_lbph.py, etc.: For model training attendance.py: For real-time recognition and attendance retrain_gui.py: A Tkinter-based GUI for model retraining The pretrained encodings and sample CSV attendance log are also included. For any academic reuse, kindly cite this Zenodo archive using the DOI provided.