Litcius/Paper detail

Analysis of the Application Efficiency of TensorFlow and PyTorch in Convolutional Neural Network

Ovidiu Constantin Novac, Mihai Cristian Chirodea, Cornelia Mihaela Novac, Nicu Bizon, Mihai Oproescu, Ovidiu Stan, Cornelia Emilia Gordan

2022Sensors61 citationsDOIOpen Access PDF

Abstract

In this paper, we present an analysis of important aspects that arise during the development of neural network applications. Our aim is to determine if the choice of library can impact the system's overall performance, either during training or design, and to extract a set of criteria that could be used to highlight the advantages and disadvantages of each library under consideration. To do so, we first extracted the previously mentioned aspects by comparing two of the most popular neural network libraries-PyTorch and TensorFlow-and then we performed an analysis on the obtained results, with the intent of determining if our initial hypothesis was correct. In the end, the results of the analysis are gathered, and an overall picture of what tasks are better suited for what library is presented.

Topics & Concepts

Computer scienceConvolutional neural networkArtificial intelligenceArtificial neural networkSet (abstract data type)Machine learningDeep learningProgramming languageNeural Networks and ApplicationsAdvanced Neural Network ApplicationsAnomaly Detection Techniques and Applications