Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep Learning
The current system to detect the bottle caps is using the HSV (Hue, Saturation and Value) technique. This technique has an accuracy of 85.938% to count the bottle caps. The accuracy of the system to count the bottle caps can be increased by implementing computer vision with deep learning. The...
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2019
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my-utp-utpedia.208792021-09-09T19:58:11Z http://utpedia.utp.edu.my/20879/ Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep Learning Saifbudin, Abdul Syahid Q Science (General) The current system to detect the bottle caps is using the HSV (Hue, Saturation and Value) technique. This technique has an accuracy of 85.938% to count the bottle caps. The accuracy of the system to count the bottle caps can be increased by implementing computer vision with deep learning. The proposed system should be able improve the accuracy to count the bottle caps. The development of the system is develop using python, computer vision and deep learning. The output of the result is expected to improve the accuracy for the detection of the bottle cap by 15 percent. IRC 2019-09 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/20879/1/Abdul%20Syahid_23033.pdf Saifbudin, Abdul Syahid (2019) Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep Learning. IRC, Universiti Teknologi PETRONAS. (Submitted) |
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Q Science (General) Saifbudin, Abdul Syahid Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep Learning |
| description |
The current system to detect the bottle caps is using the HSV (Hue, Saturation and Value)
technique. This technique has an accuracy of 85.938% to count the bottle caps. The accuracy of
the system to count the bottle caps can be increased by implementing computer vision with deep
learning. The proposed system should be able improve the accuracy to count the bottle caps. The
development of the system is develop using python, computer vision and deep learning. The
output of the result is expected to improve the accuracy for the detection of the bottle cap by 15
percent. |
| format |
Final Year Project |
| author |
Saifbudin, Abdul Syahid |
| author_facet |
Saifbudin, Abdul Syahid |
| author_sort |
Saifbudin, Abdul Syahid |
| title |
Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep
Learning |
| title_short |
Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep
Learning |
| title_full |
Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep
Learning |
| title_fullStr |
Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep
Learning |
| title_full_unstemmed |
Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep
Learning |
| title_sort |
improving the accuracy to count bottle caps by implementation of computer vision and deep
learning |
| publisher |
IRC |
| publishDate |
2019 |
| url |
http://utpedia.utp.edu.my/20879/1/Abdul%20Syahid_23033.pdf http://utpedia.utp.edu.my/20879/ |
| _version_ |
1739832806786203648 |