Object detection using machine learning techniques
Computer Vision is now an active research area under Deep Learning and Object Detection is an integral part of Computer Vision. Having a more complete idea of Deep Learning-based Object Detection Application, I start building up my own object detector for 4 classes of objects: person, car, bicycle...
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sg-ntu-dr.10356-782812023-07-07T16:05:20Z Object detection using machine learning techniques Li, Ling Huang Guangbin School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Computer Vision is now an active research area under Deep Learning and Object Detection is an integral part of Computer Vision. Having a more complete idea of Deep Learning-based Object Detection Application, I start building up my own object detector for 4 classes of objects: person, car, bicycle and motorbike. This object detector is tailored for use in Singapore and I achieve a good mAP of 42% which is much higher than the official statistics provided by TensorFlow. In addition, I not only conduct inference test on my object detector model with image inputs, but also I test it with a live stream video by using Webcam. What’s more interesting is that I deploy this object detection model in a mobile device. It can simulate the driving scenario by realizing real-time object detection. Bachelor of Engineering (Electrical and Electronic Engineering) 2019-06-14T06:41:24Z 2019-06-14T06:41:24Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78281 en Nanyang Technological University 71 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Li, Ling Object detection using machine learning techniques |
| description |
Computer Vision is now an active research area under Deep Learning and Object Detection is an integral part of Computer Vision.
Having a more complete idea of Deep Learning-based Object Detection Application, I start building up my own object detector for 4 classes of objects: person, car, bicycle and motorbike. This object detector is tailored for use in Singapore and I achieve a good mAP of 42% which is much higher than the official statistics provided by TensorFlow. In addition, I not only conduct inference test on my object detector model with image inputs, but also I test it with a live stream video by using Webcam. What’s more interesting is that I deploy this object detection model in a mobile device. It can simulate the driving scenario by realizing real-time object detection. |
| author2 |
Huang Guangbin |
| author_facet |
Huang Guangbin Li, Ling |
| format |
Final Year Project |
| author |
Li, Ling |
| author_sort |
Li, Ling |
| title |
Object detection using machine learning techniques |
| title_short |
Object detection using machine learning techniques |
| title_full |
Object detection using machine learning techniques |
| title_fullStr |
Object detection using machine learning techniques |
| title_full_unstemmed |
Object detection using machine learning techniques |
| title_sort |
object detection using machine learning techniques |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10356/78281 |
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1772826389363294208 |