6 papers
Aeroengine performance prediction using a physical-embedded data-driven method
Tong Mo, Shiran Dai, An Fu +2
Accurate and efficient prediction of aeroengine performance is of paramount importance for engine design, maintenance, and optimization endeavours. However, existing methodologies…
Leveraging Learning Metrics for Improved Federated Learning
Andre Fu
Currently in the federated setting, no learning schemes leverage the emerging research of explainable artificial intelligence (XAI) in particular the novel learning metrics that he…
P4AI: Approaching AI Ethics through Principlism
Andre Fu, Elisa Ding, Mahdi S. Hosseini +1
The field of computer vision is rapidly evolving, particularly in the context of new methods of neural architecture design. These models contribute to (1) the Climate Crisis - incr…
NoFADE: Analyzing Diminishing Returns on CO2 Investment
Andre Fu, Justin Tran, Andy Xie +6
Climate change continues to be a pressing issue that currently affects society at-large. It is important that we as a society, including the Computer Vision (CV) community take ste…
CONet: Channel Optimization for Convolutional Neural Networks
Mahdi S. Hosseini, Jia Shu Zhang, Zhe Liu +7
Neural Architecture Search (NAS) has shifted network design from using human intuition to leveraging search algorithms guided by evaluation metrics. We study channel size optimizat…
Reconsidering CO2 emissions from Computer Vision
Andre Fu, Mahdi S. Hosseini, Konstantinos N. Plataniotis
Climate change is a pressing issue that is currently affecting and will affect every part of our lives. It's becoming incredibly vital we, as a society, address the climate crisis…