Abstract:
Rock Paper Scissors (Janken/RPS) is one of the most widely played types of
games across the globe. This game is usually done to draw something or just a game to
determine a winner or a loser. Usually, this game is only played by two or more humans.
But thanks to the times and technology, RPS can now be played between humans and
computers. To realize this, a research was carried out to differentiate the shown hand
object in the shape of rocks, scissors, and paper by creating a model that is capable to do
so. In this case, classification performance is something that must be considered. To
perform the classification, an image classifier is needed. One of the widely known
classifiers is the Convolutional Neural Network (ConvNet/CNN), which is a class of
neural networks typically utilized in image classification data. The human neural network
is a source of inspiration in the creation of CNN. There are 3 stages that this algorithm
has to use, namely the pooling layers, convolutional layers, and fully-connected layers. In
this project, the final resulting model has a fairly accurate result.
