Accelerating Convolutional Neural Networks on Raspberry Pi

Unless you have been living under the rock, you must have heard of the revolution that deep learning and convolutional neural networks have brought in computer vision. Computers have achieved near-human level accuracy for most of the tasks. This problem gets worse for an application like object detection where multiple windows at different locations and scale need to be processed. Models that achieve state of the art accuracy are too large to fit into mobile devices or small devices like Raspberry Pi. Even if you somehow manage to live with the large size of models, the amount of run-time memory(RAM) required to run these models is way too high and limits their usage.