Stumbled onto a game changer for training my AI model's image recognition
I was stuck for days trying to get my model to tell apart different types of street signs, and it kept mixing up stop and yield signs. Finally decided to feed it only pictures taken in rain and fog, like 200 from a Portland dataset, and it suddenly clicked. The trick was making the training data intentionally bad or blurry, not perfect. Has anyone else tried this kind of adversarial training, or am I just lucky?