We voted yes!
Examples of Silverpond’s Deep Learning Prototypes
Virtual SCATS and counting traffic
Current traffic counting system such as SCATS can’t detect the types of vehicles in a road network. In this prototype we demonstrate the ability to count different types of vehicles using computer vision.
Object Tracking in Sports
We are using a CNN to identify a tennis ball and we implement a tracking to follow the ball.
Tracking human poses in our office
Silverpond experimenting with a CNN that detects human poses in a single web camera video feed. Possible use cases include pedestrian, limb and face detection.
Identifying gender and age
In this example, we demonstrate the ability to identify gender and age of a person. This system combines two models, one to detect the face and the other to calculate age and gender.