63 citations · 195 across the 22 of their papers we have counts for
22 papers
Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable Diffusion
Jordan Shipard, Arnold Wiliem, Kien Nguyen Thanh +2
In this work, we investigate the problem of Model-Agnostic Zero-Shot Classification (MA-ZSC), which refers to training non-specific classification architectures (downstream models)…
Does Interference Exist When Training a Once-For-All Network?
Jordan Shipard, Arnold Wiliem, Clinton Fookes
The Once-For-All (OFA) method offers an excellent pathway to deploy a trained neural network model into multiple target platforms by utilising the supernet-subnet architecture. Onc…
Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation
Siqi Yang, Lin Wu, Arnold Wiliem +1
We present a novel approach to perform the unsupervised domain adaptation for object detection through forward-backward cyclic (FBC) training. Recent adversarial training based dom…
To What Extent Does Downsampling, Compression, and Data Scarcity Impact Renal Image Analysis?
Can Peng, Kun Zhao, Arnold Wiliem +4
The condition of the Glomeruli, or filter sacks, in renal Direct Immunofluorescence (DIF) specimens is a critical indicator for diagnosing kidney diseases. A digital pathology syst…
Deep inspection: an electrical distribution pole parts study via deep neural networks
Liangchen Liu, Teng Zhang, Kun Zhao +3
Electrical distribution poles are important assets in electricity supply. These poles need to be maintained in good condition to ensure they protect community safety, maintain reli…
Deep Instance-Level Hard Negative Mining Model for Histopathology Images
Meng Li, Lin Wu, Arnold Wiliem +3
Histopathology image analysis can be considered as a Multiple instance learning (MIL) problem, where the whole slide histopathology image (WSI) is regarded as a bag of instances (i…