IMAGE CLASSIFICATION OF AGRICULTURAL DATA USING SUPERVISED LEARNING TECHNIQUES:-A SURVEY
Main Article Content
Abstract
Nowadays with the increasing progress in the field of machine learning and image processing, image classification plays a vital role and provides various advantages like to classify the different varieties of wheat/rice seeds or any other agricultural seeds/grains. The literature basically includes the algorithm for feature extraction and dimensionality reduction algorithms in order to reduce error. Accuracy totally depends on a number of the ratio of samples which are divided for training and testing phase. This survey includes an artificial neural network with back-propagation having multiple hidden layer and support vector machine, these supervised learning models are taken into consideration in order to classify the types, by which through the accuracy could be known. Various issues and challenges are highlighted in this survey. It is evident from the literature that back-propagation with multiple hidden layers can reduce more error in comparison to single layer hidden layer.
Downloads
Download data is not yet available.
Article Details
Section
Articles
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.