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Image Classification Using TensorFlow

  • Kiran Seetala
  • William Birdsong
  • Yenumula B. ReddyEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 800)

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).

Notes

Acknowledgement

This work was supported by the AFRL Minority Leaders Research Collaboration Program, contract FA8650-13-C-5800. The authors greatly acknowledge AFRL/RY for their assistance in this work.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kiran Seetala
    • 1
  • William Birdsong
    • 2
  • Yenumula B. Reddy
    • 2
    Email author
  1. 1.Department of Electrical EngineeringLouisiana Tech UniversityRustonUSA
  2. 2.Department of Computer ScienceGrambling State UniversityGramblingUSA

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