Dr Hans Ren

Tiwtor Cyfrifiadureg

Computer Science

hanchi.ren@abertawe.ac.uk

015
Llawr Gwaelod
Y Ffowndri Gyfrifiadol
Campws y Bae

Dolenni Ymchwil

ResearchGate

Google Scholar

Trosolwg

Mae Dr Hanchi Ren yn Diwtor ac yn aelod o'r Grŵp Dysgu Cyfrifiadurol a Thechnolegol (http://csvision.swan.ac.uk) yn yr Adran Gyfrifiadureg, Prifysgol Abertawe, lle cwblhaodd ei raddau PhD (2023) a MSc (2016).

Gyda llwyddiannau dysgu dwfn mewn llawer o dasgau gwybyddol cyfrifiadurol, mae AI wedi bod yn dod yn graidd i seilwaith digidol. Mae mwyafrif gwaith Dr Hanchi Ren yn perthyn yn agos i ddysgu peirianyddol cymhwysol i gynhyrchion diwydiannol a llafurus amrywiol. Felly, mae ei ddiddordeb ymchwil ac addysgu yn canolbwyntio'n bennaf ar ddatblygiad sylfaenol dysgu peiriannau damcaniaethol a'i gymwysiadau mewn gweledigaeth gyfrifiadurol, data mawr a chadw preifatrwydd.

Meysydd Arbenigedd

Golwg Cyfrifiadurol
Cadwraeth Preifatrwydd
Dysgu Peirianyddol
Dysgu Dwfn

Cyhoeddiadau

Uchafbwyntiau Ymchwil

Hu, F., Ren, H., Hu, C., Deng, J., & Xie, X. (2024). An Element-Wise Weights Aggregation Method for Federated Learning. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW)IEEE.
https://doi.org/10.1109/icdmw60847.2023.00031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66909
Watson, M., Ren, H., Arvin, F., & Hu, J. (2024). Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics. In 2024 Annual Conference Towards Autonomous Robotic Systems (TAROS)Springer.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66908
https://link.springer.com/conference/taros
Li, Y., Ren, H., Deng, J., Ma, X., & Xie, X. (2024). Centersam: Fully Automatic Prompt for Dense Nucleus Segmentation. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.
https://doi.org/10.1109/isbi56570.2024.10635872, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66747
Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, 127225
https://doi.org/10.1016/j.neucom.2023.127225, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65451
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569
https://doi.org/10.1016/j.neucom.2023.127126, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65267
Ren, H., Deng, J., & Xie, X. (2022). GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning. ACM Transactions on Intelligent Systems and Technology, 13(4)
https://doi.org/10.1145/3510032, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59093
Ren, H., Hu, F., Myint, S., Hou, K., Zhang, X., Zuo, M., Zhang, C., Zhang, Q., & Li, H. (2021). A Real-Time and Long-Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT-Based Multimedia Communication Systems. Wireless Communications and Mobile Computing, 2021, 1-15.
https://doi.org/10.1155/2021/6711561, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58621
Hu, F., Ren, H., Hu, C., Li, Y., Deng, J., & Xie, X. (2024). Gradients Stand-in for Defending Deep Leakage in Federated Learning. In International Conference on Computing in Natural Sciences, Biomedicine and Engineering
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66608
Ren, H., Wang, Y., & Ma, H. (2024). Deep Prediction Network Based on Covariance Intersection Fusion for Sensor Data. IECE Transactions on Intelligent Systematics, 1(1), 10-18.
https://doi.org/10.62762/tis.2024.136898, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67603

Holl Ymchwil

Erthyglau Cylchgronau

Ren, H., Wang, Y., & Ma, H. (2024). Deep Prediction Network Based on Covariance Intersection Fusion for Sensor Data. IECE Transactions on Intelligent Systematics, 1(1), 10-18.
https://doi.org/10.62762/tis.2024.136898, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67603
Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, 127225
https://doi.org/10.1016/j.neucom.2023.127225, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65451
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569
https://doi.org/10.1016/j.neucom.2023.127126, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65267
Ren, H., Deng, J., & Xie, X. (2022). GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning. ACM Transactions on Intelligent Systems and Technology, 13(4)
https://doi.org/10.1145/3510032, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59093
Ren, H., Hu, F., Myint, S., Hou, K., Zhang, X., Zuo, M., Zhang, C., Zhang, Q., & Li, H. (2021). A Real-Time and Long-Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT-Based Multimedia Communication Systems. Wireless Communications and Mobile Computing, 2021, 1-15.
https://doi.org/10.1155/2021/6711561, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58621

Cyfraniadau Cynadleddau

Hu, F., Ren, H., Hu, C., Li, Y., Deng, J., & Xie, X. (2024). Gradients Stand-in for Defending Deep Leakage in Federated Learning. In International Conference on Computing in Natural Sciences, Biomedicine and Engineering
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66608
Li, Y., Ren, H., Deng, J., Ma, X., & Xie, X. (2024). Centersam: Fully Automatic Prompt for Dense Nucleus Segmentation. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.
https://doi.org/10.1109/isbi56570.2024.10635872, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66747
Watson, M., Ren, H., Arvin, F., & Hu, J. (2024). Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics. In 2024 Annual Conference Towards Autonomous Robotic Systems (TAROS)Springer.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66908
https://link.springer.com/conference/taros
Hu, F., Ren, H., Hu, C., Deng, J., & Xie, X. (2024). An Element-Wise Weights Aggregation Method for Federated Learning. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW)IEEE.
https://doi.org/10.1109/icdmw60847.2023.00031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66909