| Autor: |
Hussah Albinali, Fatimah Abdulraheem Alzahrani |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
2021 International Conference of Women in Data Science at Taif University (WiDSTaif ). |
| DOI: |
10.1109/widstaif52235.2021.9430211 |
| Popis: |
Object detection is a computer vision problem that involves classifying objects and identifying their location in a picture, video, or webcam feed. Applying deep learning techniques to this problem has led to huge contributions and attracted much research in this field. In this work, we use Faster RCNN to detect objects in micrograph images that have been manually annotated. We considered a Faster RCNN model because of its speed and its high accuracy of detection. The objective of this work is to detect objects in medical images and to evaluate the performance of Faster RCNN for medical images. We also compared the detecting highly overlapped objects and non-overlapping objects. Our experiment included 65 micrograph images with approximately 1000 objects, with findings that demonstrate that Faster RCNN obtained highly accurate results with mPA 76% for non overlapping objects. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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