Bronchop Neumonia Detection Using Novel Multilevel Deep Neural Network Schema
- Title
- Bronchop Neumonia Detection Using Novel Multilevel Deep Neural Network Schema
- Creator
- Prasanna K.R.; Vijayakumar R.; Sevam J.D.; Parthasarathy P.
- Description
- Pneumonia is a dangerous disease that can occur in one or both lungs and is usually caused by a virus, fungus or bacteria. Respiratory syncytial virus (RSV) is the most common cause of pneumonia in children. With the development of pneumonia, it can be divided into four stages: congestion, red liver, gray liver and regression. In our work, we employ the most powerful tools and techniques such as VGG16, an object recognition and classification algorithm that can classify 1000 images in 1000 different groups with 92.7% accuracy. It is one of the popular algorithms designed for image classification and simple to use by means of transfer learning. Transfer learning (TL) is a technique in deep learning that spotlight on pre-learning the neural network and storing the knowledge gained while solving a problem and applying it to new and different information. In our work, the information gained by learning about 1000 different groups on Image Net can be used and strive to identify diseases. 2023 EDP Sciences. All rights reserved.
- Source
- E3S Web of Conferences, Vol-399
- Date
- 2023-01-01
- Publisher
- EDP Sciences
- Coverage
- Prasanna K.R., Bharat Institute of Higher Education and Research, Chennai, India; Vijayakumar R., Lakshmi Narayana Institute of Medical Science, Puduchery, India; Sevam J.D., School of Business and Management, Christ Deemed to Be University, Banglore, India; Parthasarathy P., Ece Department, Psna College of Engineering and Technology, Dindigul, India
- Rights
- All Open Access; Gold Open Access; Green Open Access
- Relation
- ISSN: 25550403
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Prasanna K.R.; Vijayakumar R.; Sevam J.D.; Parthasarathy P., “Bronchop Neumonia Detection Using Novel Multilevel Deep Neural Network Schema,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/19599.