Computer visionVehicle detection, tracking, plate recognition and event records from live camera feeds.
Service · Hassan Revel
Computer vision & ML.
Hassan develops computer vision workflows for detection, tracking, classification and video analytics. The work connects model output to an interface and records that people can use.
Discuss this service
01 · The work
Define what needs to be detected
A video feed contains more information than most workflows need. Hassan starts with the objects, events and evidence a team needs to review, then shapes the model pipeline and data collection around those requirements.
02 · The work
Build the surrounding application
Detection and tracking are connected to APIs, stored records and a review interface. For traffic workflows, that can include vehicle information, plate recognition, event timestamps and captured frames.
03 · The work
Evaluate under realistic conditions
Camera angles, image quality and changes in the environment affect a vision application. Testing uses representative inputs and examines the errors that matter to the intended workflow. Performance targets are defined for the actual deployment environment.
A practical starting point
Send the current workflow, available data and intended outcome. Hassan can use that context to define the scope, integrations and delivery steps.
Discuss the scopeRelated work
The service, in practice.
Computer vision