Using guard feedback to train AI models

This system helps train artificial intelligence models to understand what's happening in videos. It works by taking recorded video from a camera, breaking it into individual frames, and then trying to identify objects and classify events based on their characteristics like movement, size, or color. The system then shows these identified objects and events to a user for feedback, and based on how the user responds, it learns and adjusts its understanding to become better at recognizing things in future videos.

Why it matters: Filed before the widespread availability of advanced MLOps platforms and specialized data labeling tools. These advancements now make it more efficient to manage video data, integrate human feedback, and iteratively train AI models as described.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedHeavy software system, AI model, video processing

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