That is activation mapping. I understood that what he was suggesting is using another objective that is optimized to define why network decided what it did. But

That is activation mapping. I understood that what he was suggesting is using another objective that is optimized to define why network decided what it did. But need loss function for that For let’s say identifying a car we could come up with a labeled dataset that not only has classes but also different parts of the car labeled that we think differentiate car from a motorcycle or a whatever. Then model has to output both class and also segmentation or bounding boxes of the parts Then we combine both losses from these outputs and train. I tried using unet by attaching layers to it in different ways to interpret the segmentation. I could not get it to work well though