It’s been one month already, and during this time I’ve collected a dataset from the objects found in the Allard Pierson museum. This dataset consists of pictures from the objects from all angles, and is used to train the computer such that it will be able to recognise these objects when you take a picture of them.
Based on the objects from the Allard Pierson museum we can conclude that it will be much more beneficial to move away from the individual hieroglyph recognition, and focus more on detecting the objects as a whole. This brings a few advantages such as a higher classification rate and real-time classification, which means that the App will recognise the object as soon as it appears in front of the camera.
Currently, one of the most promising methods for this task is based on an Artificial Neural Network, which tries to mimic the behaviour of real brain cells. Much research has been conducted in this particular field of study, as a biological brain is still the most advanced phenomenon when it comes to recognising visual input.
