Location, Landmarking
Identify faces inside an edge, produce key focuses on the face, and start following stay time and session time. Pass that location into our neural systems for our socioeconomics.
Neural Network
When we identify and milestone, the location is passed to our neural system to create a chain of command of highlights, to contrast with our current model of what our socioeconomics should resemble.
Produce Demographics
From that point, we create age, sexual orientation, and feeling for identified individual and push these measurements to the dashboard, trigger webhooks, and store in our database.
Precision and Metrics
The following are refreshed measurable examination of the exactness of our information focuses. We enhance these day by day and will develop the sorts of measurements we assemble as we further build up our innovation stage.
Metrics Accuracy (%)
Happy 80.5
Angry 83.3
Surprised 91.1
Fear 82.6 http://muzun.ae/technology.htmlhttp://muzun.ae/technology.html
Sad 78.1
Disgust 98.5
Calm 80.8
Metrics Accuracy (%)
Male 91.3
Female 91.3
Age +/ - 10 years
View +/ - 5 degrees (91.3%)
Abide Time +/ - 100 ms
Uniqueness and Occlusion Algorithms
We utilize a blend of complex following and location calculations to keep up an individual's session over the screen.
Our mind boggling calculations can deal with impediments, blocks, and lost identifications, to keep up the uniqueness of an individual over the session.
A client's "session" is considered from the time the face is first identified, till an interim of time that the face can never again be recognized.
Low Latency
Our Computer Vision calculations consider low idleness executions, on ease equipment arrangements on location, or remotely.
We've improved our discoveries to process faces as low as 2 milliseconds for each face at a separation of roughly 25-30 feet.
Range
Our Computer Vision innovation can be connected to any number of cameras with short and long-extend vision.
The nature of our measurements are autonomous of the range, and simply dependent on the pixel measurements of the discoveries.
Our testing extent and least location measure is 30x30 pixels, at a separation of 25 feet, and can be reached out with higher goals cameras.
Multi-Platform Support
Our libraries were intended to be effortlessly deployable and bolster both OpenCV and OpenCL combinations.
On the best way to begin with our SDKs, it would be ideal if you reach us.
Identify faces inside an edge, produce key focuses on the face, and start following stay time and session time. Pass that location into our neural systems for our socioeconomics.
Neural Network
When we identify and milestone, the location is passed to our neural system to create a chain of command of highlights, to contrast with our current model of what our socioeconomics should resemble.Produce Demographics
From that point, we create age, sexual orientation, and feeling for identified individual and push these measurements to the dashboard, trigger webhooks, and store in our database.
Precision and Metrics
The following are refreshed measurable examination of the exactness of our information focuses. We enhance these day by day and will develop the sorts of measurements we assemble as we further build up our innovation stage.
Metrics Accuracy (%)
Happy 80.5
Angry 83.3Surprised 91.1
Fear 82.6 http://muzun.ae/technology.htmlhttp://muzun.ae/technology.html
Sad 78.1
Disgust 98.5
Calm 80.8
Metrics Accuracy (%)
Male 91.3
Female 91.3
Age +/ - 10 years
View +/ - 5 degrees (91.3%)
Abide Time +/ - 100 ms
Uniqueness and Occlusion Algorithms
We utilize a blend of complex following and location calculations to keep up an individual's session over the screen.
Our mind boggling calculations can deal with impediments, blocks, and lost identifications, to keep up the uniqueness of an individual over the session.
A client's "session" is considered from the time the face is first identified, till an interim of time that the face can never again be recognized.
Low Latency
Our Computer Vision calculations consider low idleness executions, on ease equipment arrangements on location, or remotely.
We've improved our discoveries to process faces as low as 2 milliseconds for each face at a separation of roughly 25-30 feet.
Range
Our Computer Vision innovation can be connected to any number of cameras with short and long-extend vision.
The nature of our measurements are autonomous of the range, and simply dependent on the pixel measurements of the discoveries.
Our testing extent and least location measure is 30x30 pixels, at a separation of 25 feet, and can be reached out with higher goals cameras.
Multi-Platform Support
Our libraries were intended to be effortlessly deployable and bolster both OpenCV and OpenCL combinations.
On the best way to begin with our SDKs, it would be ideal if you reach us.
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