This is a follow-up question from my previous post here about explosion detection. I gathered a dataset of explosions. As I'm new to Deep Learning in Keras, I'm trying to see what architecture best suits this problem, given that here we have a cloud of smoke/fire as opposed to an object. Any suggestions?
For instance, I've learned about Faster RCNN or RetinaNet, but that is mostly for object detection. Is it going to be better than say a basic ResNet50? And here real-time prediction requirements are not an issue. So shall I assume a heavier model (e.g. NASNet Large or a Resnet-152 model) is better than a basic ResNet-50 model?