Comparative analysis on YOLO object detection with OpenCV
Computer Vision is a field of study that helps to develop techniques to identify images and displays. It has various features like image recognition, object detection and image creation, etc. Object detection is used for face detection, vehicle detection, web images, and safety systems. Its algorith...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ayandegan Institute of Higher Education,
2020-03-01
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| Series: | International Journal of Research in Industrial Engineering |
| Subjects: | |
| Online Access: | http://www.riejournal.com/article_106905_afd0caf26202eb3ac3b605fd17894255.pdf |
| Summary: | Computer Vision is a field of study that helps to develop techniques to identify images and displays. It has various features like image recognition, object detection and image creation, etc. Object detection is used for face detection, vehicle detection, web images, and safety systems. Its algorithms are Region-based Convolutional Neural Networks (RCNN), Faster-RCNN and You Only Look Once Method (YOLO) that have shown state-of-the-art performance. Of these, YOLO is better in speed compared to accuracy. It has efficient object detection without compromising on performance. |
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| ISSN: | 2783-1337 2717-2937 |