MD Nafees Chand
Dinesh Sahu
- Student Department of Computer Science and Engineering, RKDF Institute of Science and Technology, Bhopal Madhya Pradesh India
- Professor Department of Computer Science and Engineering, RKDF Institute of Science and Technology, Bhopal Madhya Pradesh India
Abstract
Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved via the use of deep neural networks to aid with picture classification. A neural network is a kind of pattern-recognition computer system. The structure of the human brain served as inspiration for its design, thus the name. Input, hidden, as well as output layers make up these layers. The Inception V3 model was used in the suggested work in order to categorize a picture into many categories such as animal, person, selfie, group shot, location, vehicle, etc. Rather than relying on picture feature extraction or image segmentation, this research provides a new way for more precise image categorization. An encouraging 99.6% accuracy was achieved in the intended task using proposed model Inception V3.
Keywords: Deep learning, Inception V3, image classification, neural network, image segmentation.
[This article belongs to Journal of Telecommunication, Switching Systems and Networks(jotssn)]
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Journal of Telecommunication, Switching Systems and Networks
| Volume | 11 |
| Issue | 01 |
| Received | May 5, 2024 |
| Accepted | May 16, 2024 |
| Published | May 27, 2024 |