Helmet violation detection using deep learning | |
| Author | K.C., Dharma Raj |
| Call Number | AIT Thesis no.CS-17-03 |
| Subject(s) | Traffic regulations Pattern recognition systems Machine learning Neural networks (Computer science) |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. CS-17-03 |
| Abstract | Today, road accidents are one of the major causes of human deaths. Among the different type of road accidents, motorcycle accidents are common in Asia and cause severe injuries. The helmet is the main protection device for motorcyclists. Most countries have rules for use of helmets but many people fail to follow these rules for various reasons. One solution is a robust system that can find the motorcyclists who are violating helmet rules and record the evidence necessary for legal action. This thesis paper presents the use of deep convolutional neural networks (DCNNs) for finding motorcyclists who are violating helmet rules. I describe incremental development of a DCNN and an evaluation in terms of accuracy and speed for finding motorcyclists who are violating the helmet use rules. The license plate character DCNN provides highly accurate and fast character recognition of Thailand license plates. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis : no. CS-17-03 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Dailey, Matthew N.; |
| Examination Committee(s) | Mongkol Ekpanyapong;Guha, Sumanta; |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2017 |