37 citations · 53 across the 7 of their papers we have counts for
10 papers
Weakly Supervised Learning for cell recognition in immunohistochemical cytoplasm staining images
Shichuan Zhang, Chenglu Zhu, Honglin Li +2
Cell classification and counting in immunohistochemical cytoplasm staining images play a pivotal role in cancer diagnosis. Weakly supervised learning is a potential method to deal…
Generalizing Nucleus Recognition Model in Multi-source Images via Pruning
Jiatong Cai, Chenglu Zhu, Can Cui +4
Ki67 is a significant biomarker in the diagnosis and prognosis of cancer, whose index can be evaluated by quantifying its expression in Ki67 immunohistochemistry (IHC) stained imag…
An attention model to analyse the risk of agitation and urinary tract infections in people with dementia
Honglin Li, Roonak Rezvani, Magdalena Anita Kolanko +5
Behavioural symptoms and urinary tract infections (UTI) are among the most common problems faced by people with dementia. One of the key challenges in the management of these condi…
Deep Representation for Connected Health: Semi-supervised Learning for Analysing the Risk of Urinary Tract Infections in People with Dementia
Honglin Li, Magdalena Anita Kolanko, Shirin Enshaeifar +13
Machine learning techniques combined with in-home monitoring technologies provide a unique opportunity to automate diagnosis and early detection of adverse health conditions in lon…
Semi-supervised Federated Learning for Activity Recognition
Yuchen Zhao, Hanyang Liu, Honglin Li +2
Training deep learning models on in-home IoT sensory data is commonly used to recognise human activities. Recently, federated learning systems that use edge devices as clients to s…
Verifying the Causes of Adversarial Examples
Honglin Li, Yifei Fan, Frieder Ganz +2
The robustness of neural networks is challenged by adversarial examples that contain almost imperceptible perturbations to inputs, which mislead a classifier to incorrect outputs i…