Floriculture classification using simple neural network and deep learning

Shrikant Dharwadkar, Ganesh Bhat, N. V. Subba Reddy, Prakash K. Aithal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an approach based on deep learning for identification and classification of flowers to aid in domains such as patent analysis of flowers and floriculture industry. The Deep convolutional network using its pre-Trained knowledge shows the potential for accurate identification of flowers than the present existing approaches for image classification. The study reveals that the use of deep learning neural network comparatively increases the accuracy to identify the flowers consisting of high semantic features over the simple neural network built from scratch.

Original languageEnglish
Title of host publicationRTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages619-622
Number of pages4
Volume2018-January
ISBN (Electronic)9781509037049
DOIs
Publication statusPublished - 12-01-2017
Event2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017 - Bangalore, India
Duration: 19-05-201720-05-2017

Conference

Conference2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017
CountryIndia
CityBangalore
Period19-05-1720-05-17

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Media Technology
  • Control and Optimization
  • Instrumentation
  • Transportation
  • Communication

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    Dharwadkar, S., Bhat, G., Subba Reddy, N. V., & Aithal, P. K. (2017). Floriculture classification using simple neural network and deep learning. In RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings (Vol. 2018-January, pp. 619-622). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTEICT.2017.8256671