Image Classification Using TensorFlow

Title: Image Classification Using TensorFlow
Creator(s): Seetala, Kiran; Birdsong, William; Reddy, Yenumula B.
Editor(s): Latifi, Shahram
Date: 2019
Is Part Of: 16th International Conference on Information Technology-New Generations (ITNG 2019)
In Series: Advances in Intelligent Systems and Computing
Pages: 485-488
Language: eng
Publisher: Springer International Publishing
Place Published: Cham
ISBN: 978-3-030-14070-0
DOI: https://doi.org/10.1007/978-3-030-14070-0_67
Zotero BiDiAr: https://www.zotero.org/groups/5293298/bidiar/items/CDFDY6L8/item-list
Abstract: Deep learning (DL) is a process that consists of a set of methods which classifies the raw data into meaningful information fed into the machine. DL performs classification tasks directly from sound, text, and images. One of the famous algorithms for classification of images in DL is convolutional neural networks (CNN). In this research, we tested DL model for image recognition using TensorFlow from Dockers software. We received 99% accurate to identify the test image. The system configuration used for this research includes Ubuntu 16.04, Python 2.7, TensorFlow 1.9, and Google image set (Fatkun Batch Download Image: Google, Google, chrome.google.com/webstore/detail/fatkun-batch-download-ima/nnjjahlikiabnchcpehcpkdeckfgnohf).

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