IEEE transactions on medical imaging
Jul 30, 2021
Large, fine-grained image segmentation datasets, annotated at pixel-level, are difficult to obtain, particularly in medical imaging, where annotations also require expert knowledge. Weakly-supervised learning can train models by relying on weaker for...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jul 30, 2021
Good performance and high efficiency are both critical for estimating human pose in practice. Recent state-of-the-art methods have greatly boosted the pose detection accuracy through deep convolutional neural networks, however, the strong performance...
IEEE journal of biomedical and health informatics
Jul 27, 2021
Non-used clinical information has negative implications on healthcare quality. Clinicians pay priority attention to clinical information relevant to their specialties during routine clinical practices but may be insensitive or less concerned about in...
IEEE journal of biomedical and health informatics
Jul 27, 2021
Recently, an emerging trend in medical image classification is to combine radiomics framework with deep learning classification network in an integrated system. Although this combination is efficient in some tasks, the deep learning-based classificat...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jul 21, 2021
Human-Object Interaction (HOI) Detection is an important task to understand how humans interact with objects. Most of the existing works treat this task as an exhaustive triplet 〈 human, verb, object 〉 classification problem. In this paper, we decomp...
Journal of biomedical informatics
Jul 18, 2021
BACKGROUND: Recent natural language processing (NLP) research is dominated by neural network methods that employ word embeddings as basic building blocks. Pre-training with neural methods that capture local and global distributional properties (e.g.,...
Journal of biomedical semantics
Jul 18, 2021
BACKGROUND: Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially f...
Human brain mapping
Jul 15, 2021
In order to describe how humans represent meaning in the brain, one must be able to account for not just concrete words but, critically, also abstract words, which lack a physical referent. Hebbian formalism and optimization are basic principles of b...
Journal of biomedical semantics
Jul 15, 2021
BACKGROUND: Recent advances in representation learning have enabled large strides in natural language understanding; However, verbal reasoning remains a challenge for state-of-the-art systems. External sources of structured, expert-curated verb-relat...
Sensors (Basel, Switzerland)
Jul 14, 2021
In this work, we investigated two issues: (1) How the fusion of lidar and camera data can improve semantic segmentation performance compared with the individual sensor modalities in a supervised learning context; and (2) How fusion can also be levera...