Low-Power Face Recognition Using Joint Optical and Electronic Deep Neural Networks
Xuening Dong, Bokun Zhao, Hassan Rahbardar Mojaver, Odile Liboiron-Ladouceur, Brett H. Meyer · IEEE Embedded Systems Letters · 2025
Power and energy constraints limit the implementation of deep face recognition algorithms on edge devices. To address this issue, we propose an electro-optic hybrid system, with an always-on optical neural network that continuously monitors faces in a given environment and activates deep face recognition when a face is detected. We adapt the system for a scenario similar to a smart door lock application, involving center-aligned, randomly appearing faces. Tested on the Labeled Faces in the Wild dataset, the proposed system achieves 95.8% accuracy with 16 features extracted from face images by principal components analysis and enables a remarkable 33.2% reduction in power usage compared to the same neural network on digital processors.