Helmet & Number Plate Detection & Recognition |
Author(s): |
| Shubham Ugale , Sandip Institute of Technology and Research Centre (SITRC); Prof. Abhay R. Gaidhani, Sandip Institute of Technology and Research Centre (SITRC); Rutik Shelke, Sandip Institute of Technology and Research Centre (SITRC); Pratima Jadhav, Sandip Institute of Technology and Research Centre (SITRC); Sahil Dyandyan, Sandip Institute of Technology and Research Centre (SITRC) |
Keywords: |
| Helmet, Security System, Vehicle Riders |
Abstract |
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Helmet wearing is very important for the safety of two Vehicle riders. But main problem is how to do surveillance whether the person is wearing helmet or not is difficult. Detecting objects in images and videos is a difficult task of. Most of the algorithms for object detection are sensitive to background clutter and occlusion, and cannot localize the edge of the object. An objects shape is typically the most discriminative cue for its recognition by humans. Based on the YOLO V3 full-regression deep neural network architecture, using convolution and dark net we can successfully detect the helmet this paper deals with the object detection using YOLO. |
Other Details |
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Paper ID: IJSRDV11I10023 Published in: Volume : 11, Issue : 1 Publication Date: 01/04/2023 Page(s): 16-18 |
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