Autonomous Persistent Wide Area Surveillance of Human and Vehicle Activity Defence and Security Accelerator (Ref: DSTL0000007030, ACC6031106): £93,978, Post-Doctoral Research Fellow (PI: Prof. Toby P. Breckon) Received from The Ministry of Defence (DASA), UK, 2022-2023 Project Page
Tracking Drones Across Different Platforms with Machine Vision Security Technology Research Innovation Grants Programme (S-TRIG) (Ref: 007CD): £32,727, Research Assistant (PI: Hubert P. H. Shum) () Received from The Catapult Network (S-TRIG), UK, 2020-2021 Project Page
Yona Falinie A. Gaus, Neelanjan Bhowmik, Brian K. S. Isaac-Medina, Hubert P. H. Shum, Amir Atapour-Abarghouei and Toby P. Breckon, "Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery," in CVPRW '23: Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 2995-3005, Vancouver, Canada, IEEE/CVF, Jun 2023.
Bibtex
@inproceedings{gaus23region, author={Gaus, Yona Falinie A. and Bhowmik, Neelanjan and Isaac-Medina, Brian K. S. and Shum, Hubert P. H. and Atapour-Abarghouei, Amir and Breckon, Toby P.}, booktitle={Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops}, series={CVPRW '23}, title={Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery}, year={2023}, month={6}, pages={2995--3005}, numpages={11}, doi={10.1109/CVPRW59228.2023.00301}, publisher={IEEE/CVF}, location={Vancouver, Canada}, }
RIS
TY - CONF AU - Gaus, Yona Falinie A. AU - Bhowmik, Neelanjan AU - Isaac-Medina, Brian K. S. AU - Shum, Hubert P. H. AU - Atapour-Abarghouei, Amir AU - Breckon, Toby P. T2 - Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops TI - Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery PY - 2023 Y1 - 6 2023 SP - 2995 EP - 3005 DO - 10.1109/CVPRW59228.2023.00301 PB - IEEE/CVF ER -
< ref name="gaus23region">{{cite conference |last1=Gaus |first1=Yona Falinie A. |last2=Bhowmik |first2=Neelanjan |last3=Isaac-Medina |first3=Brian K. S. |last4=Shum |first4=Hubert P. H. |last5=Atapour-Abarghouei |first5=Amir |last6=Breckon |first6=Toby P. |title=Region-Based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery |date=2023 |pages=2995--3005 |doi=10.1109/CVPRW59228.2023.00301 |publisher=IEEE/CVF |url=http://doi.org/10.1109/CVPRW59228.2023.00301 }}< /ref>
Daniel Organisciak, Matthew Poyser, Aishah Alsehaim, Shanfeng Hu, Brian K. S. Isaac-Medina, Toby P. Breckon and Hubert P. H. Shum, "UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery," in VISAPP '22: Proceedings of the 2022 International Conference on Computer Vision Theory and Applications, pp. 136-146, SciTePress, Feb 2022.
Bibtex
@inproceedings{organisciak22uavreid, author={Organisciak, Daniel and Poyser, Matthew and Alsehaim, Aishah and Hu, Shanfeng and Isaac-Medina, Brian K. S. and Breckon, Toby P. and Shum, Hubert P. H.}, booktitle={Proceedings of the 2022 International Conference on Computer Vision Theory and Applications}, series={VISAPP '22}, title={UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery}, year={2022}, month={2}, pages={136--146}, numpages={11}, doi={10.5220/0010836600003124}, isbn={978-989-758-555-5}, publisher={SciTePress}, }
RIS
TY - CONF AU - Organisciak, Daniel AU - Poyser, Matthew AU - Alsehaim, Aishah AU - Hu, Shanfeng AU - Isaac-Medina, Brian K. S. AU - Breckon, Toby P. AU - Shum, Hubert P. H. T2 - Proceedings of the 2022 International Conference on Computer Vision Theory and Applications TI - UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery PY - 2022 Y1 - 2 2022 SP - 136 EP - 146 DO - 10.5220/0010836600003124 SN - 978-989-758-555-5 PB - SciTePress ER -
< ref name="organisciak22uavreid">{{cite conference |last1=Organisciak |first1=Daniel |last2=Poyser |first2=Matthew |last3=Alsehaim |first3=Aishah |last4=Hu |first4=Shanfeng |last5=Isaac-Medina |first5=Brian K. S. |last6=Breckon |first6=Toby P. |last7=Shum |first7=Hubert P. H. |title=UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery |date=2022 |pages=136--146 |doi=10.5220/0010836600003124 |isbn=978-989-758-555-5 |publisher=SciTePress |url=https://arxiv.org/abs/2104.06219 }}< /ref>
Brian K. S. Isaac-Medina, Matthew Poyser, Daniel Organisciak, Chris G. Willcocks, Toby P. Breckon and Hubert P. H. Shum, "Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark," in ICCVW '21: Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision Workshops, pp. 1223-1232, IEEE/CVF, Oct 2021.
Bibtex
@inproceedings{issacmedina21unmanned, author={Isaac-Medina, Brian K. S. and Poyser, Matthew and Organisciak, Daniel and Willcocks, Chris G. and Breckon, Toby P. and Shum, Hubert P. H.}, booktitle={Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision Workshops}, series={ICCVW '21}, title={Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark}, year={2021}, month={10}, pages={1223--1232}, numpages={10}, doi={10.1109/ICCVW54120.2021.00142}, publisher={IEEE/CVF}, }
RIS
TY - CONF AU - Isaac-Medina, Brian K. S. AU - Poyser, Matthew AU - Organisciak, Daniel AU - Willcocks, Chris G. AU - Breckon, Toby P. AU - Shum, Hubert P. H. T2 - Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision Workshops TI - Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark PY - 2021 Y1 - 10 2021 SP - 1223 EP - 1232 DO - 10.1109/ICCVW54120.2021.00142 PB - IEEE/CVF ER -
< ref name="issacmedina21unmanned">{{cite conference |last1=Isaac-Medina |first1=Brian K. S. |last2=Poyser |first2=Matthew |last3=Organisciak |first3=Daniel |last4=Willcocks |first4=Chris G. |last5=Breckon |first5=Toby P. |last6=Shum |first6=Hubert P. H. |title=Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark |date=2021 |pages=1223--1232 |doi=10.1109/ICCVW54120.2021.00142 |publisher=IEEE/CVF |url=https://arxiv.org/abs/2103.13933 }}< /ref>