1. Technological advancement

Deep learning has achieved unprecedented performance in the field of Artificial Intelligence. However, due to the complexity of deep model, its deployment in practical applications with limited computing and storage resources such as mobile devices, edge devices and real-time systems becomes a difficult and painful point. In this technology, a model compression technology based on knowledge distillation is proposed for face recognition obscured by masks. The lightweight student model obtained by learning can be applied and deployed to the edge computing platform with limited resources.

2. Technology maturity

This technology is based on knowledge distillation of depth model compression, and presents a new face recognition technology for mask occlusion facing edge intelligence. Knowledge distillation is a hot topic in model compression research in recent years. It is a simple and effective model compression technology, which has been developed and used by google, Baidu and Tencent.

3. Situation of intellectual property rights

This technology is supported by Jiangsu University and has been supported by the National Natural Science Foundation.

4. Expected benefits and types of enterprises to cooperate with

The technique is an edge intelligent algorithm, which can be used for face and image recognition on edge computing platform.