Dharwadkar, Shrikant and Bhat, Ganesh and Reddy, Subba N V and Aithal, Prakash K (2017) Floriculture Classification using Simple Neural Network and Deep Learning. In: International Conference On Recent Trends In Electronics Information Communication Technology, 19/05/2017, Bangalore India.
![]() |
PDF
746.pdf - Published Version Restricted to Registered users only Download (440kB) | Request a copy |
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
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Uncontrolled Keywords: | Deep Learning, Transfer Learning, Convolutional Neural Network, Computer Vision, Image Classification |
Subjects: | Engineering > MIT Manipal > Computer Science and Engineering |
Depositing User: | MIT Library |
Date Deposited: | 23 Jun 2017 10:19 |
Last Modified: | 23 Jun 2017 10:19 |
URI: | http://eprints.manipal.edu/id/eprint/149148 |
Actions (login required)
![]() |
View Item |