Envisioning Deep Learning Networks

Deep learning techniques are referred to as 'black box models' because of its opaque nature. Interpretability techniques and explainable methods help to make the complex network transparent and explain the user why a particular decision is made by the model. Different visualization techniques used for the interpretation of deep learning networks for both image and non-image classification are investigated in this paper.