An Attendance Checking System on Mobile Devices Using Transfer Learning

IoT applications have been used in many contexts, especially applications on mobile devices. This work presents an attendance checking system by identifying and recognizing human faces on mobile devices using a transfer learning approach. This system includes a mobile application and a web application. These two applications are communicated by using APIs. The mobile application detects human faces by using the camera on that mobile device, then, the face features are extracted using the FaceNet model, and finally, the attendees are identified by computing similarity with existing faces in the database. The proposed system was tested on a dataset with 358 images of 52 employees in our office. Results show that the accuracy is about 93.46% on the test set and 97.06% in the real environment. Thus, this system could be used for checking attendances in several real contexts.