most citedFew-shot Semantic Segmentation with Self-supervision from Pseudo-classes

9 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20219 cited

Few-shot Semantic Segmentation with Self-supervision from Pseudo-classes

Yiwen Li, Gratianus Wesley Putra Data, Yunguan Fu +2

Despite the success of deep learning methods for semantic segmentation, few-shot semantic segmentation remains a challenging task due to the limited training data and the generalis…

eess.IV2021

Real-time multimodal image registration with partial intraoperative point-set data

Zachary M C Baum, Yipeng Hu, Dean C Barratt

We present Free Point Transformer (FPT) - a deep neural network architecture for non-rigid point-set registration. Consisting of two modules, a global feature extraction module and…

eess.IV20212 cited

Lung Ultrasound Segmentation and Adaptation between COVID-19 and Community-Acquired Pneumonia

Harry Mason, Lorenzo Cristoni, Andrew Walden +6

Lung ultrasound imaging has been shown effective in detecting typical patterns for interstitial pneumonia, as a point-of-care tool for both patients with COVID-19 and other communi…

cs.CV2021

Adaptable image quality assessment using meta-reinforcement learning of task amenability

Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8

The performance of many medical image analysis tasks are strongly associated with image data quality. When developing modern deep learning algorithms, rather than relying on subjec…

cs.CV2021

Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels

Liam F Chalcroft, Jiongqi Qu, Sophie A Martin +8

When developing deep neural networks for segmenting intraoperative ultrasound images, several practical issues are encountered frequently, such as the presence of ultrasound frames…