Kim, Junghoon Yun, Sang-Seok Choi, Jongsuk Kim, Daijin Kang, Bong-Nam 2024-01-19T11:07:58Z 2024-01-19T11:07:58Z 2022-02-28 2017-06 2325-033X https://pubs.kist.re.kr/handle/201004/114639 Recently, deep convolutional neural networks (DCNNs) have set a new trend in the computer vision community by improving the state-of-the-art performance in almost all of applications. We propose DCNN-based face recognition algorithm. This paper aims at analyzing and verifying considerations when the proposed method is implemented in a real environment. First, Multiple images of the same scene are processed. Also, this novel method is considered together with a method to reduce the total recognition time in the perspective of integrated system. We analyzed the experimental data and evaluated the performance by setting up the sensor fusion network in actual classroom. English IEEE Reliable Multi-Person Identification Using DCNN-Based Face Recognition Algorithm and Scale-Ratio Method Conference 1 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp.97 - 101 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 97 101 US Jeju, SOUTH KOREA 2017-06-28 2017 14TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI) 000426976900021 2-s2.0-85034246604