Dr Yuanbo Wu

Uwch-ddarlithydd, Computer Science

l.y.wu@abertawe.ac.uk

223
Ail lawr
Y Ffowndri Gyfrifiadol
Campws y Bae

Ar gael ar gyfer Goruchwyliaeth Ôl-raddedig

Dolenni Ymchwil

Google Scholar

ResearcherID

Trosolwg

Derbyniodd Dr Lin Yuanbo Wi ei PhD o Brifysgol De Cymru Newydd, Kensington, Sydney, Awstralia yn 2014. Mae gan Dr Wu ddiddordebau ymchwil eang ar draws tasgau gweledigaeth gyfrifiadurol a dysgu peirianyddol, gyda chymhelliad cryf i fynd i’r afael â heriau’r byd go iawn. Mae Dr Wu yn arbenigo mewn deall cynnwys fideos (megis rhannu fframiau fideos/panoptig/segmentiad gwrthrychau, canfod/olrhain gwrthrych), ailnodi gwrthrych, dysgu cynyddol, deallusrwydd artiffisial cynhyrchiol a datblygiadau deallusrwydd artiffisial ar gyfer astudiaethau meddygol. Ar hyn o bryd, mae Dr Wu yn Olygydd Cysylltiol gydag IEEE Trans on Neural Networks and Learning Systems (IF: 14.255), IEEE Trans on Multimedia (IF: 8.182) ac IEEE Trans on Big Data (IF: 4.271). Mae Dr Wu yn uwch-aelod o IEEE.

Meysydd Arbenigedd

Gweld â chymorth cyfrifiadur
Canfod gwrthrych
Olrhain sawl gwrthrych
Segmentu enghreifftiau o delweddau a gwrthrych a segmentu panoptig
Dysgu peirianyddol
Deallusrwydd artiffisial ar gyfer biowyddoniaeth

Uchafbwyntiau Gyrfa

Ymchwil

Cyhoeddiadau:

Pseudo-Pair Based Self-Similarity Learning for Unsupervised Person Re-Identification. Lin Wu, Deyin Liu, Wenying Zhang, Dapeng Chen, Zongyuan Ge, Farid Boussaid, Mohammed Bennamoun, Jialie Shen, Yuanbo Wu. Journal article1/1/2022IEEE Transactions on Image Processing314803-4816
10.1109/tip.2022.3186746

Cyhoeddiadau

Uchafbwyntiau Ymchwil

Liu, D., Wu, Y., Hong, R., Ge, Z., Shen, J., Boussaid, F., & Bennamoun, M. (2023). Generative Metric Learning for Adversarially Robust Open-world Person Re-Identification. ACM Transactions on Multimedia Computing, Communications, and Applications, 19(1), 1-19.
https://doi.org/10.1145/3522714, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63558
http://dx.doi.org/10.1145/3522714
Wu, Y., Liu, D., Guo, X., Hong, R., Liu, L., & Zhang, R. (2022). Multi-scale Spatial Representation Learning via Recursive Hermite Polynomial Networks. In Proceedings of the Thirty-First International Joint Conference on Artificial IntelligenceInternational Joint Conferences on Artificial Intelligence Organization.
https://doi.org/10.24963/ijcai.2022/204, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63557
http://dx.doi.org/10.24963/ijcai.2022/204
Wu, Y., Wang, Y., Gao, J., Wang, M., Zha, Z., & Tao, D. (2021). Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 722-735.
https://doi.org/10.1109/tnnls.2020.2979190, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63200
http://dx.doi.org/10.1109/tnnls.2020.2979190
Lin, Z., Zhang, D., Shi, D., Xu, R., Tao, Q., Wu, Y., He, M., & Ge, Z. (2023). Contrastive pre-training and linear interaction attention-based transformer for universal medical reports generation. Journal of Biomedical Informatics, 138, 104281
https://doi.org/10.1016/j.jbi.2023.104281, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63181
http://dx.doi.org/10.1016/j.jbi.2023.104281
Liu, D., Wu, Y., Zheng, F., Liu, L., & Wang, M. (2022). Verbal-Person Nets: Pose-Guided Multi-Granularity Language-to-Person Generation. IEEE Transactions on Neural Networks and Learning Systems, 1-13.
https://doi.org/10.1109/tnnls.2022.3151631, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63180
http://dx.doi.org/10.1109/tnnls.2022.3151631
Hu, C., Xie, X., & Wu, Y. (2023). Face reenactment via generative landmark guidance. Image and Vision Computing, 130, 104611
https://doi.org/10.1016/j.imavis.2022.104611, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62159
Ji, Z., Hu, J., Liu, D., Wu, Y., & Zhao, Y. (2022). Asymmetric Cross-Scale Alignment for Text-Based Person Search. IEEE Transactions on Multimedia, 0, 1-11.
https://doi.org/10.1109/tmm.2022.3225754, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62251
Wu, Y., Liu, D., Zhang, W., Chen, D., Ge, Z., Boussaid, F., Bennamoun, M., & Shen, J. (2022). Pseudo-Pair Based Self-Similarity Learning for Unsupervised Person Re-Identification. IEEE Transactions on Image Processing, 31, 4803-4816.
https://doi.org/10.1109/tip.2022.3186746, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa61771

Holl Ymchwil

Erthyglau Cylchgronau

Lin, Z., Zhang, D., Shi, D., Xu, R., Tao, Q., Wu, Y., He, M., & Ge, Z. (2023). Contrastive pre-training and linear interaction attention-based transformer for universal medical reports generation. Journal of Biomedical Informatics, 138, 104281
https://doi.org/10.1016/j.jbi.2023.104281, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63181
http://dx.doi.org/10.1016/j.jbi.2023.104281
Hu, C., Xie, X., & Wu, Y. (2023). Face reenactment via generative landmark guidance. Image and Vision Computing, 130, 104611
https://doi.org/10.1016/j.imavis.2022.104611, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62159
Liu, D., Wu, Y., Hong, R., Ge, Z., Shen, J., Boussaid, F., & Bennamoun, M. (2023). Generative Metric Learning for Adversarially Robust Open-world Person Re-Identification. ACM Transactions on Multimedia Computing, Communications, and Applications, 19(1), 1-19.
https://doi.org/10.1145/3522714, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63558
http://dx.doi.org/10.1145/3522714
Ji, Z., Hu, J., Liu, D., Wu, Y., & Zhao, Y. (2022). Asymmetric Cross-Scale Alignment for Text-Based Person Search. IEEE Transactions on Multimedia, 0, 1-11.
https://doi.org/10.1109/tmm.2022.3225754, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62251
Wu, Y., Liu, D., Zhang, W., Chen, D., Ge, Z., Boussaid, F., Bennamoun, M., & Shen, J. (2022). Pseudo-Pair Based Self-Similarity Learning for Unsupervised Person Re-Identification. IEEE Transactions on Image Processing, 31, 4803-4816.
https://doi.org/10.1109/tip.2022.3186746, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa61771
Liu, D., Wu, Y., Zheng, F., Liu, L., & Wang, M. (2022). Verbal-Person Nets: Pose-Guided Multi-Granularity Language-to-Person Generation. IEEE Transactions on Neural Networks and Learning Systems, 1-13.
https://doi.org/10.1109/tnnls.2022.3151631, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63180
http://dx.doi.org/10.1109/tnnls.2022.3151631
Wu, Y., Wang, Y., Gao, J., Wang, M., Zha, Z., & Tao, D. (2021). Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 722-735.
https://doi.org/10.1109/tnnls.2020.2979190, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63200
http://dx.doi.org/10.1109/tnnls.2020.2979190

Cyfraniadau Cynadleddau

Wu, Y., Liu, D., Guo, X., Hong, R., Liu, L., & Zhang, R. (2022). Multi-scale Spatial Representation Learning via Recursive Hermite Polynomial Networks. In Proceedings of the Thirty-First International Joint Conference on Artificial IntelligenceInternational Joint Conferences on Artificial Intelligence Organization.
https://doi.org/10.24963/ijcai.2022/204, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63557
http://dx.doi.org/10.24963/ijcai.2022/204

Goruchwyliaeth

Untitled (cyfredol)

PhD

Goruchwyliwr arall: Prof Xianghua Xie

Modiwlau a Addysgir

CSC371 Advanced Object-Oriented Programming

This module will give an advanced look at object-oriented programming (OOP) languages. It will investigate how OOP languages and libraries evolved to meet the needs of developers, overcoming the challenges involved in application development using non-OOP languages. The module introduces the programming languages C and C++, including low-level aspects of programming that are usually abstracted away in languages like Java. By starting with C, students will gain an in-depth understanding of the need for OOP concepts before moving on to studying programming in C++ and these concepts.