YOLOv8-Based Deep Learning Model for Detection of Bacterial Inhibition Zones
Abstract
This project presents a YOLOv8-based deep learning system for automatic detection of bacterial inhibition zones from plate images. The model demonstrates high precision and recall, indicating reliability, and performs well despite a small dataset. This approach can improve antimicrobial susceptibility testing by saving time and reducing human error, offering a valuable tool for microbiology laboratories.
Fields of Study & Subjects
Advanced Neural Network Applications
Cell Image Analysis Techniques
Industrial Vision Systems and Defect Detection
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 February 2026
- Language
- EN