Project · Artificial Intelligence (AI)
Ship a real-time defect detector
Train, quantise and deploy a detection model on a webcam feed with a latency budget. Includes the dataset, the deployment target and the rubric.
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The brief
Week 1: dataset audit and baseline training. Week 2: quantisation and export, measure latency. Week 3: integrate with the camera loop, add a confidence threshold and a review queue.
What you submit: model card, latency table, a two-minute recording and the review-queue design.
Rubric emphasises the trade-off you chose between precision and latency, and how you justified it.