78 citations · 290 across the 25 of their papers we have counts for
8 papers · 1 filter
IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer
Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
Automated medical report generation has become increasingly important in medical analysis. It can produce computer-aided diagnosis descriptions and thus significantly alleviate the…
A Randomized Block Krylov Method for Tensor Train Approximation
Gaohang Yu, Jinhong Feng, Zhongming Chen +2
Tensor train decomposition is a powerful tool for dealing with high-dimensional, large-scale tensor data, which is not suffering from the curse of dimensionality. To accelerate the…
Proximal nested sampling with data-driven priors for physical scientists
Jason D. McEwen, Tobías I. Liaudat, Matthew A. Price +2
Proximal nested sampling was introduced recently to open up Bayesian model selection for high-dimensional problems such as computational imaging. The framework is suitable for mode…
A Bilevel Formalism for the Peer-Reviewing Problem
Gennaro Auricchio, Ruixiao Zhang, Jie Zhang +1
Due to the large number of submissions that more and more conferences experience, finding an automatized way to well distribute the submitted papers among reviewers has become nece…
Few-shot Learning for Inference in Medical Imaging with Subspace Feature Representations
Jiahui Liu, Keqiang Fan, Xiaohao Cai +1
Unlike the field of visual scene recognition where tremendous advances have taken place due to the availability of very large datasets to train deep neural networks, inference from…
GO-LDA: Generalised Optimal Linear Discriminant Analysis
Jiahui Liu, Xiaohao Cai, Mahesan Niranjan
Linear discriminant analysis (LDA) has been a useful tool in pattern recognition and data analysis research and practice. While linearity of class boundaries cannot always be expec…
Semantic Segmentation by Semantic Proportions
Halil Ibrahim Aysel, Xiaohao Cai, Adam Prügel-Bennett
Semantic segmentation is a critical task in computer vision aiming to identify and classify individual pixels in an image, with numerous applications in for example autonomous driv…
Practical Sketching Algorithms for Low-Rank Tucker Approximation of Large Tensors
Wandi Dong, Gaohang Yu, Liqun Qi +1
Low-rank approximation of tensors has been widely used in high-dimensional data analysis. It usually involves singular value decomposition (SVD) of large-scale matrices with high c…