The accuracy of 1 million Megaface interference set and Facescrub prob set with noise removed reaches over 98%. The accuracy of the test set of face recognition in non-cooperative business scenes reaches over 96%.

It can accurately identify a variety of face attribute information, including age, gender, emotion, mask, glasses, etc.

The frame difference method and mean background modeling method are used to detect the moving point set in the current frame. The moving point set is spatially meshed by 8 x 8. The LSD algorithm is employed to calculate the main direction of the moving segment of the mesh.

It can accurately identify a variety of pedestrian attribute information, including whether the pedestrian wears short sleeves, backpacks, skirts, blue pants or trousers, etc.

The implementation cost is low. AI technology is employed to analyze whether payment and collection behaviors actually occur at the cash register through video. The accuracy of real scene is over 99%.

Based on the intelligent morning meeting detection algorithm, judge whether there are enough people standing together for the morning meeting within the preset time range and whether the requirement for the preset time of the morning meeting is met, so as to accurately judge whether the morning meeting task is completed as required.

Detect and identify all kinds of staff and passengers, and give early warning in case of intrusion of passengers.

On the basis of pedestrian detection and tracking, all people in a certain range can be identified to locate the position and trajectory of a target person accurately. Besides, it supports cross-camera tracking.

By analyzing the pixel changes between the front and rear key frames in a video, we can judge whether there are target behaviors in the video, such as digging the sewer and scratching the skin with the spoon, bending down to pick up things, so as to supervise the operation of kitchen staff.

Analyze what behaviors and actions all people in the video are doing to supervise the operation of vehicle maintenance personnel.

Analyze what behaviors and actions all people in the video are doing to supervise the operation of vehicle maintenance personnel.

Judge whether the target object exists from an image, and determine the coordinate position of the existing target object in the image.

Check whether the green plants are placed as required.

Check whether the lifeguard leaves the post and give a warning in time according to the time of absence.

Monitor the service status of the station.

It intelligently identifies obstacles and filters non-obstacles based on the deep learning. When there are obstacles in the fire passage, it can send out reminders in time to realize intelligent fire prevention.

The technologies of back modeling, trajectory tracking, track determination and pattern recognition and classification are adopted to realize accurate mice detection based on the process management of moving trajectory tracking, normal trajectory pattern determination and classifier classification.

In the process of playing the piano, it can give prompt of wrong fingering in time, realize intelligent teaching, solve the problem of shortage of teachers, and greatly improve teaching efficiency.