segmentation and classification and detection are done on a Pascal dataset which is much smaller than imagenet so you can think of the advantage of P training as hey if you don't have too many labels you know you really need some kind of features to start with to be able to perform the task and semantic segmentation are also on Pascal VLC but a different version of the dataset 2012 and that uses another architecture like fully convolution that for doing the semantic segmentation part so using the feed train part of context