Paper Title
An AI Enabled Framework for Bacteria Detection from Microscopic Images for Biomedical Applications
Article Identifiers
Authors
Dr. Amitha I C , A K Rithul , Akash M , Amarnath T , Drishyap K
Keywords
YOLOv5 algorithm, Traditional laboratory testing, YOLOv5 architecture, Bacteria detection and classification, CNN, Documentation.
Abstract
Bacteria in waterbodies are a significant concern in today’s world due to their potential impact on human health, ecosystems, and water quality. Traditional laboratory testing methods have been the primary approach for bacteria detection. However, these methods are often characterized by lengthy processing time, the need for skilled labor, and significant resource investments. These limitations underscore the need for alternative approaches that offer faster, more efficient, and cost-effective solutions for bacteria detection and water quality monitoring. Thus, we propose an innovative AI-enabled framework for the detection of bacteria in water samples, designed to overcome the limitations of traditional methods. This system reduces analysis time and resource needs significantly by automating the identification process using the YOLOv5 algorithm and advanced image processing techniques. It offers a complete solution for effective and precise bacteria identification, with consequences for public health, water quality management, and environmental monitoring.
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How To Cite (APA)
Dr. Amitha I C, A K Rithul, Akash M, Amarnath T, & Drishyap K (July-2024). An AI Enabled Framework for Bacteria Detection from Microscopic Images for Biomedical Applications . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), f688-f698. https://ijnrd.org/papers/IJNRD2407469.pdf
Issue
Volume 9 Issue 7, July-2024
Pages : f688-f698
Other Publication Details
Paper Reg. ID: IJNRD_225897
Published Paper Id: IJNRD2407469
Downloads: 000121991
Research Area: Computer Science & TechnologyÂ
Country: Kannur, Kerala, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2407469.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407469
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
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Licence
This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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