mbar0075/SaRLVision
A reinforcement learning object detector leveraging saliency ranking, offering a self-explainable system with a fully observable action log. | B.Sc. IT (Hons) Artificial Intelligence Dissertation | University of Malta Dean's List Awards 2024
This project helps operations engineers and quality control managers identify and classify objects within images with an added layer of transparency. You feed it an image, and it outputs bounding boxes around detected objects, along with an explanation of how it arrived at that conclusion through an observable action log. This is ideal for those who need to understand the reasoning behind AI decisions in critical applications.
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Use this if you need to detect objects in images and require a clear, step-by-step understanding of how the system made its detection decisions, rather than just getting a final result.
Not ideal if your primary concern is only raw detection speed or achieving the absolute highest detection accuracy without any need for interpretability.
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Jupyter Notebook
License
MIT
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Last pushed
May 28, 2025
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