Object detection and image cropping using a multi-detector approach

This invention describes a smart way to find objects in digital pictures. It uses several different detection methods, each with its own settings or algorithms, to analyze the image. Then, it compares the results from all these methods, picks the best one based on how confident each method is, and uses that to identify the objects. The method is specifically designed to detect multiple distinct objects using multiple different detectors.

Why it matters: Filed as AI models were becoming highly specialized. The past three years have seen significant advancements in orchestrating multiple AI models, improving confidence scoring, and fusing diverse outputs, making this multi-detector approach more robust and performant.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, image processing algorithms, machine learning models

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