Comparison of Tensorflow and PyTorch in Convolutional Neural Network - based Applications
Mihai Cristian Chirodea, Ovidiu Constantin Novac, Cornelia Mihaela Novac, Nicu Bizon, Mihai Oproescu, Cornelia Emilia Gordan
Abstract
In this paper, we present a comparison between the PyTorch and TensorFlow environments, used in defining neural networks. The purpose is to find whether the choice of a library affects the overall performance of the system both during training and design. To do so, our approach involves analysis of the processes involved when creating a neural network, as well as taking measurements and monitoring its evolution over the epochs. Advantages and disadvantages are then extracted from the results and are then used to draw conclusions.
Topics & Concepts
Computer scienceConvolutional neural networkArtificial intelligenceArtificial neural networkDeep learningMachine learningRecurrent neural networkDeep neural networksAnomaly Detection Techniques and ApplicationsAdvanced Neural Network ApplicationsNeural Networks and Applications