Abstract
Lung & Colon cancer are amongst the leading cause of cancer related deaths worldwide. In this study, we used a five-class lung and colon cancer histopathology dataset and applied various image preprocessing techniques such as contrast stretching, unsharp masking, and resizing. We then trained a ResNetl01 model on this preprocessed dataset and achieved a high accuracy of 99.7%. The increased reliability and robustness of deep learning-based histopathology classifiers with high performance computers can enable instantaneous and automated diagnosis which can further help treatment and recovery.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350334395 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023 - Bangalore, India Duration: 14-07-2023 → 16-07-2023 |
Publication series
| Name | Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies |
|---|
Conference
| Conference | 9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023 |
|---|---|
| Country/Territory | India |
| City | Bangalore |
| Period | 14-07-23 → 16-07-23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Information Systems
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
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