Classical machine learning models require all the data to be available prior to the training. Once a model is trained on certain tasks, it is limited to perform on those tasks and cannot be adopted to solve a different problem. But in the dynamic world that we are living, there is no end to a stream of data coming from different sources. Incremental learning or lifelong learning is a hot research area that studies the ability of neural networks to continuously learn new knowledge while retaining old experiences, imitating the human way of learning. One of the proposed approaches is to rehearse previously learned information when learning a new class of samples.