A Study on the Influence of Geometric Transformations on Image Classification: A Case Study

Title

A Study on the Influence of Geometric Transformations on Image Classification: A Case Study

Creator

Nellisara S.D.; Dutta J.; Cyriac S.

Description

The present research work involves the study of the geometrical transformations which influences the training and validation accuracies of machine learning models. For the study, rice plant leaf disease dataset of 2096 images consisting of 4 classes with 523 images per class were used. The dataset subjected to 24 models out of which three models namely - DenseNet201, Densenet169 and InceptionResNetV2 are selected based on highest training accuracy and less difference between training and validation accuracy. To evaluate the performance of the selected three models, loss functions and accuracies have been computed. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-290, pp. 411-416.

Date

2021-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Augmentation; DenseNet; InceptionResNet; Rice plant leaf disease

Coverage

Nellisara S.D., Center for Advanced Research and Training, CHRIST (Deemed To Be University), Bangalore, India; Dutta J., Center for Digital Innovation, CHRIST (Deemed To Be University), Bangalore, India; Cyriac S., Center for Digital Innovation, CHRIST (Deemed To Be University), Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981164485-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-16-4486-3_46

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115066625&doi=10.1007%2f978-981-16-4486-3_46&partnerID=40&md5=f58ec2789639a02cc7faf598e3b851f5