Image Classification in Monkey Species using Image Classifiers of Keras
A species is biologically basic classification and taxonomic rank of an organism. Among the many common names for the mammals that make up the suborder Simiiformes (sometimes known as the simians), “monkey” is among the most common. The traditional classification of all members of the group currently known as simians as monkeys. Different classifiers are used to categorize the various kinds of monkeys based on their photos. Assigning a name or class to an image is the work of image classification. In the research paper, different image classifiers of Keras are used for image classification in monkey species. A dataset of 10 distinct monkey species was used to test out many different classifiers. Keras comes preloaded with a variety of Convolutional Neural Networks, including VGG16, VGG19, ResNet50, ResNet-50 V2, ResNeXt101, Inception V3, and Xception. We compared the performance of other classifiers and discovered that ResNeXt-101 achieved the best accuracy (99.98%).
Authors
- Neelam Singh (ORCID: https://orcid.org/0000-0002-5340-3714)
- Manisha Upreti
- Ankita Dwivedi (ORCID: https://orcid.org/0009-0009-9746-5560)
- Vandana Rawat (ORCID: https://orcid.org/0000-0003-3190-5163)
Institutions
- Graphic Era University (IN)
Publication Details
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1109/ssitcon62437.2024.10796327
- Primary Topic
- Digital Imaging for Blood Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00