Dr Daniel Organisciak

Northumbria University
PhD (Co-supervised with )
, 2018 - 2022

Northumbria University
, UK

Downloads


Grants Involved

The Catapult Network (S-TRIG)
Tracking Drones Across Different Platforms with Machine Vision
Security Technology Research Innovation Grants Programme (S-TRIG) (Ref: 007CD): £32,727, Contributing Researcher (PI: Hubert P. H. Shum) ()
Received from The Catapult Network (S-TRIG), UK, 2020-2021
Project Page
Northumbria University

Postgraduate Research Scholarship (Ref: ): £65,000, PhD (PI: Hubert P. H. Shum) ()
Received from Faculty of Engineering and Environment, Northumbria University, UK, 2018-2021
Project Page

Publications with the Team

RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis
RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis Impact Factor: 7.5Top 25% Journal in Computer Science, Artificial IntelligenceCitation: 26#
Expert Systems with Applications (ESWA), 2022
Daniel Organisciak, Hubert P. H. Shum, Ephraim Nwoye and Wai Lok Woo
Webpage Cite This Plain Text
Daniel Organisciak, Hubert P. H. Shum, Ephraim Nwoye and Wai Lok Woo, "RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis," Expert Systems with Applications, vol. 201, pp. 117158, Elsevier, 2022.
Bibtex
@article{organisciak22robin,
 author={Organisciak, Daniel and Shum, Hubert P. H. and Nwoye, Ephraim and Woo, Wai Lok},
 journal={Expert Systems with Applications},
 title={RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis},
 year={2022},
 volume={201},
 pages={117158},
 numpages={12},
 doi={10.1016/j.eswa.2022.117158},
 issn={0957-4174},
 publisher={Elsevier},
}
RIS
TY  - JOUR
AU  - Organisciak, Daniel
AU  - Shum, Hubert P. H.
AU  - Nwoye, Ephraim
AU  - Woo, Wai Lok
T2  - Expert Systems with Applications
TI  - RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis
PY  - 2022
VL  - 201
SP  - 117158
EP  - 117158
DO  - 10.1016/j.eswa.2022.117158
SN  - 0957-4174
PB  - Elsevier
ER  - 
Paper
UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery
UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery
Proceedings of the 2022 International Conference on Computer Vision Theory and Applications (VISAPP), 2022
Daniel Organisciak, Matthew Poyser, Aishah Alsehaim, Shanfeng Hu, Brian K. S. Isaac-Medina, Toby P. Breckon and Hubert P. H. Shum
Webpage Cite This Plain Text
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  - 
Paper GitHub
Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark
Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark H5-Index: 80#Citation: 94#
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021
Brian K. S. Isaac-Medina, Matthew Poyser, Daniel Organisciak, Chris G. Willcocks, Toby P. Breckon and Hubert P. H. Shum
Webpage Cite This Plain Text
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  - 
Paper GitHub
Unifying Person and Vehicle Re-Identification
Unifying Person and Vehicle Re-Identification Impact Factor: 3.4Citation: 14#
IEEE Access, 2020
Daniel Organisciak, Dimitrios Sakkos, Edmond S. L. Ho, Nauman Aslam and Hubert P. H. Shum
Webpage Cite This Plain Text
Daniel Organisciak, Dimitrios Sakkos, Edmond S. L. Ho, Nauman Aslam and Hubert P. H. Shum, "Unifying Person and Vehicle Re-Identification," IEEE Access, vol. 8, pp. 115673-115684, IEEE, 2020.
Bibtex
@article{daniel20unifying,
 author={Organisciak, Daniel and Sakkos, Dimitrios and Ho, Edmond S. L. and Aslam, Nauman and Shum, Hubert P. H.},
 journal={IEEE Access},
 title={Unifying Person and Vehicle Re-Identification},
 year={2020},
 volume={8},
 pages={115673--115684},
 numpages={12},
 doi={10.1109/ACCESS.2020.3004092},
 issn={2169-3536},
 publisher={IEEE},
}
RIS
TY  - JOUR
AU  - Organisciak, Daniel
AU  - Sakkos, Dimitrios
AU  - Ho, Edmond S. L.
AU  - Aslam, Nauman
AU  - Shum, Hubert P. H.
T2  - IEEE Access
TI  - Unifying Person and Vehicle Re-Identification
PY  - 2020
VL  - 8
SP  - 115673
EP  - 115684
DO  - 10.1109/ACCESS.2020.3004092
SN  - 2169-3536
PB  - IEEE
ER  - 
Paper GitHub
Makeup Style Transfer on Low-Quality Images with Weighted Multi-Scale Attention
Makeup Style Transfer on Low-Quality Images with Weighted Multi-Scale Attention H5-Index: 56#Citation: 13#
Proceedings of the 2020 International Conference on Pattern Recognition (ICPR), 2020
Daniel Organisciak, Edmond S. L. Ho and Hubert P. H. Shum
Webpage Cite This Plain Text
Daniel Organisciak, Edmond S. L. Ho and Hubert P. H. Shum, "Makeup Style Transfer on Low-Quality Images with Weighted Multi-Scale Attention," in ICPR '20: Proceedings of the 2020 International Conference on Pattern Recognition, pp. 6011-6018, Milan, Italy, Jan 2020.
Bibtex
@inproceedings{organisciak20makeup,
 author={Organisciak, Daniel and Ho, Edmond S. L. and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2020 International Conference on Pattern Recognition},
 series={ICPR '20},
 title={Makeup Style Transfer on Low-Quality Images with Weighted Multi-Scale Attention},
 year={2020},
 month={1},
 pages={6011--6018},
 numpages={8},
 doi={10.1109/ICPR48806.2021.9412604},
 location={Milan, Italy},
}
RIS
TY  - CONF
AU  - Organisciak, Daniel
AU  - Ho, Edmond S. L.
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2020 International Conference on Pattern Recognition
TI  - Makeup Style Transfer on Low-Quality Images with Weighted Multi-Scale Attention
PY  - 2020
Y1  - 1 2020
SP  - 6011
EP  - 6018
DO  - 10.1109/ICPR48806.2021.9412604
ER  - 
Paper Supplementary Material GitHub YouTube
Triplet Loss with Channel Attention for Person Re-Identification
Triplet Loss with Channel Attention for Person Re-Identification Citation: 12#
Journal of WSCG - Proceedings of the 2019 International Conferences in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG), 2019
Daniel Organisciak, Chirine Riachy, Nauman Aslam and Hubert P. H. Shum
Webpage Cite This Plain Text
Daniel Organisciak, Chirine Riachy, Nauman Aslam and Hubert P. H. Shum, "Triplet Loss with Channel Attention for Person Re-Identification," Journal of WSCG, vol. 27, no. 2, pp. 161-169, Plzen, Czech Republic, 2019.
Bibtex
@article{organisciak19triplet,
 author={Organisciak, Daniel and Riachy, Chirine and Aslam, Nauman and Shum, Hubert P. H.},
 journal={Journal of WSCG},
 title={Triplet Loss with Channel Attention for Person Re-Identification},
 year={2019},
 volume={27},
 number={2},
 pages={161--169},
 numpages={9},
 doi={10.24132/JWSCG.2019.27.2.9},
 issn={1213-6972},
 location={Plzen, Czech Republic},
}
RIS
TY  - JOUR
AU  - Organisciak, Daniel
AU  - Riachy, Chirine
AU  - Aslam, Nauman
AU  - Shum, Hubert P. H.
T2  - Journal of WSCG
TI  - Triplet Loss with Channel Attention for Person Re-Identification
PY  - 2019
VL  - 27
IS  - 2
SP  - 161
EP  - 169
DO  - 10.24132/JWSCG.2019.27.2.9
SN  - 1213-6972
ER  - 
Paper
Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptors and Fisher Vectors for Visual Action Recognition
Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptors and Fisher Vectors for Visual Action Recognition
Proceedings of the 2018 British Machine Vision Conference Workshop on Image Analysis for Human Facial and Activity Recognition (IAHFAR), 2018
Zheming Zuo, Daniel Organisciak, Hubert P. H. Shum and Longzhi Yang
Webpage Cite This Plain Text
Zheming Zuo, Daniel Organisciak, Hubert P. H. Shum and Longzhi Yang, "Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptors and Fisher Vectors for Visual Action Recognition," in IAHFAR '18: Proceedings of the 2018 British Machine Vision Conference Workshop on Image Analysis for Human Facial and Activity Recognition, Newcastle upon Tyne, UK, Sep 2018.
Bibtex
@inproceedings{zuo18saliency,
 author={Zuo, Zheming and Organisciak, Daniel and Shum, Hubert P. H. and Yang, Longzhi},
 booktitle={Proceedings of the 2018 British Machine Vision Conference Workshop on Image Analysis for Human Facial and Activity Recognition},
 series={IAHFAR '18},
 title={Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptors and Fisher Vectors for Visual Action Recognition},
 year={2018},
 month={9},
 numpages={11},
 location={Newcastle upon Tyne, UK},
}
RIS
TY  - CONF
AU  - Zuo, Zheming
AU  - Organisciak, Daniel
AU  - Shum, Hubert P. H.
AU  - Yang, Longzhi
T2  - Proceedings of the 2018 British Machine Vision Conference Workshop on Image Analysis for Human Facial and Activity Recognition
TI  - Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptors and Fisher Vectors for Visual Action Recognition
PY  - 2018
Y1  - 9 2018
ER  - 
Paper

Links

Webpage
Webpage
Google Scholar
Google Scholar
ResearchGate
ResearshGate

HomeGoogle ScholarYouTubeLinkedInTwitter/XGitHubORCIDResearchGateEmail
 
Print