This question is related to a new hobby project i want to start. I have some experience with ML techniques and neural networks, although only for regression problems as of now.
In my classification problem i get an image of multiple game cards, like those of a trading card game. I want to identify which card is shown automatically.
I have thought of template matching and neural networks.
Template matching because the cards are exactly identical everytime, so i figured they are not hard to detect. But what changes is the angle and lighting of the pictures and i have heard template matching often fails for this.
Then i can use neural networks, which are very robust in those terms. I figure there are already some proven models existing, although something like AlexNet may be a bit too complex for my problem?
Is it advisable to use a neural network? If yes, what model should i use? Or is there a better machine learning technique that suits my needs?