Real-time drone classification and detection using deep learning
This report is written to document and sum up all the findings and research of the Final Year Project. The aim is to achieve real-time drone detection with a static camera. The method used in this research project is utilizing deep learning methods in computer vision where convolutional neural netwo...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/150642 |
| _version_ | 1811694313845817344 |
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| author | Thadani, Jashan Vishindas |
| author2 | Sameer Alam |
| author_facet | Sameer Alam Thadani, Jashan Vishindas |
| author_sort | Thadani, Jashan Vishindas |
| collection | NTU |
| description | This report is written to document and sum up all the findings and research of the Final Year Project. The aim is to achieve real-time drone detection with a static camera. The method used in this research project is utilizing deep learning methods in computer vision where convolutional neural networks are primarily used to train the built model over an appropriate dataset such that after training, it would be able to work in real-time on new pieces of data input into it. The models built consists of two units: Classification and Detection, in which they both work in tandem to achieve working results. The classifier looks at a portion of given frame or image and determines whether it is a drone image or not and the detector looks a the entire frame to determine which region the drone image is likely to be in. The objectives were met by the end of this final year project and some decent results were obtained. In real-time, the model and classifier can detect a drone in an untested video footage with a high level of accuracy and relatively quick speed. The limitations of the model built is that it requires a powerful computing device to achieve the same results in higher frames per second. |
| first_indexed | 2024-10-01T07:05:36Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/150642 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:05:36Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1506422021-06-09T02:11:19Z Real-time drone classification and detection using deep learning Thadani, Jashan Vishindas Sameer Alam School of Mechanical and Aerospace Engineering Saab Singapore Pte. Ltd. sameeralam@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Aeronautical engineering This report is written to document and sum up all the findings and research of the Final Year Project. The aim is to achieve real-time drone detection with a static camera. The method used in this research project is utilizing deep learning methods in computer vision where convolutional neural networks are primarily used to train the built model over an appropriate dataset such that after training, it would be able to work in real-time on new pieces of data input into it. The models built consists of two units: Classification and Detection, in which they both work in tandem to achieve working results. The classifier looks at a portion of given frame or image and determines whether it is a drone image or not and the detector looks a the entire frame to determine which region the drone image is likely to be in. The objectives were met by the end of this final year project and some decent results were obtained. In real-time, the model and classifier can detect a drone in an untested video footage with a high level of accuracy and relatively quick speed. The limitations of the model built is that it requires a powerful computing device to achieve the same results in higher frames per second. Bachelor of Engineering (Aerospace Engineering) 2021-06-09T02:11:19Z 2021-06-09T02:11:19Z 2021 Final Year Project (FYP) Thadani, J. V. (2021). Real-time drone classification and detection using deep learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150642 https://hdl.handle.net/10356/150642 en C071 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Aeronautical engineering Thadani, Jashan Vishindas Real-time drone classification and detection using deep learning |
| title | Real-time drone classification and detection using deep learning |
| title_full | Real-time drone classification and detection using deep learning |
| title_fullStr | Real-time drone classification and detection using deep learning |
| title_full_unstemmed | Real-time drone classification and detection using deep learning |
| title_short | Real-time drone classification and detection using deep learning |
| title_sort | real time drone classification and detection using deep learning |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Aeronautical engineering |
| url | https://hdl.handle.net/10356/150642 |
| work_keys_str_mv | AT thadanijashanvishindas realtimedroneclassificationanddetectionusingdeeplearning |