On-premise deployment is an inference method that deploys deep learning models on local servers or terminal devices. Data does not need to be uploaded to the cloud, which can ensure data privacy and security, and avoid the impact of network latency. It is suitable for scenarios with high requirements for real-time performance and data confidentiality.
