In human-AI collaboration systems for critical applications, in order to...
Variational autoencoders (VAEs) are powerful generative modelling method...
Performance of convolutional neural networks (CNNs) in image analysis ta...
Blind deconvolution is an ill-posed problem arising in various fields ra...
Supervised deep learning-based methods yield accurate results for medica...
Deep neural networks (DNNs) are notorious for making more mistakes for t...
Quantifying segmentation uncertainty has become an important issue in me...
Probabilistic modelling has been an essential tool in medical image anal...
Deep neural networks achieve significant advancement to the state-of-the...
A key requirement for the success of supervised deep learning is a large...
Data driven segmentation is an important initial step of shape prior-bas...
In this paper, we propose an efficient pseudo-marginal Markov chain Mont...
Segmenting images of low quality or with missing data is a challenging
p...