I am doing a deep learning project in which i have to identify different models of cars. i am a bit confused for the following reason:
first is what algorithm should I use. I have studied that RCNNs are good algorithms that might work with my project but they are slow; will a faster RCNN reduce accuracy?
next is the training data set. I am going to use my own data set which is about 200 images for each model. Is this data sufficient
for training? Also, what should I know/how should I label and preprocess the data for training?