2021 · 21 citations · 6 references
EngineeringMachine LearningBiometricsIntelligent SystemsFace DetectionFacial Recognition SystemImage AnalysisPattern RecognitionVision RecognitionLibrary Attendance SystemMachine VisionObject DetectionComputer ScienceAutomation SystemComputer VisionYolov5 AlgorithmFacial Expression RecognitionHuman IdentificationEye Tracking
Recognizing a large number of faces at the same time is an algorithmic and computational challenge. The integration of a facial recognition system with an existing automation system in a library is also a big challenge because of the many sub-systems that operate in it. The aim is to develop a prototype of a library attendance system to assist library management related to facial recognition of users who visit the library. This study uses image processing focuses on object detection using the YOLOv5 algorithm. The library attendance system integrates 3 sub-systems: API service, face recognition using YOLOv5, and visitor identification system. The results obtained are that the library attendance system can function properly, can read the API service, and display information on the results of face detection therefore the system can be used by the existing library automation system.
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EfficientDet: Scalable and Efficient Object Detection
Mingxing Tan, Ruoming Pang, Quoc V. Le · 2020 · 7.9K citations
Convolutional Neural Network, Machine Vision, Image Analysis +14
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
Chien-Yao Wang, Hong-Yuan Mark Liao, Yueh-Hua Wu et al. · 2020 · 4.5K citations
Convolutional Neural Network, Engineering, Machine Learning +16