The SOPHON AI mini SE3 is a deep learning-based edge computing box. It is equipped with the TPU chip BM1682 independently developed by Sophon. The floating point 32-bit peak computing power is up to 3TFLOPS. It can process 4 channels of HD video at the same time.With diversified algorithms, it can realize face comparison, control analysis, video structure, object recognition, etc.
It can be connected to different types of collection devices to calculate the nearest data to achieve real-time response and edge control
Deploy various intelligent algorithms and applications of customers and partners to achieve rapid AI empowerment for various industry application scenarios
The "edge-cloud" collaborative distributed architecture distributes the computing load between the edge and the cloud, which can not only achieve scalable and ultra-large-scale management, but also have the characteristics of real-time response and control of the edge
Support up to 50,000 face database, 0.5 second for each recognition
Support 4 video streams recognition or 10 image stream recognition
Support various algorithms such as person / vehicle / non-vehicle/ object recognition, video structuring, trajectory analysis, etc.
Support smart Park / smart security / industrial application / business application and other fields and scenarios for flexible deployment
Support Caffe / TensorFlow / PyTorch / MXNet / Paddle Lite and other mainstream deep learning frameworks
Support multiple intelligent algorithms such as face recognition, vehicle recognition, object recognition, video structure, behavior analysis, etc
BMNNSDK (SOPHON Neural Network SDK) one-stop toolkit provides a series of software tools such as the underlying driver environment, compiler, inference deployment tool and so on. Easy to use and convenient, covering the model optimization, efficient runtime support and other capabilities required for the neural network inference stage, providing easy-to-use and efficient full-stack solutions for deep learning application development and deployment. BMNNSDK minimizes the development cycle and cost of algorithms and software. Users can quickly deploy deep learning algorithms on various AI hardware products of Fortune Group to facilitate intelligent applications.
4-core [email protected]
Peak computing power 3TFLOPS
Memory and storage
Length * width * height
210mm * 115mm * 45mm
Power supply and power consumption
Typical power consumption
≤35W (depending on the configuration)
Temperature and humidity
-10℃ ~ +45℃
10% ~ 90%, no condensation