Deep High-Resolution Representation Learning for Visual Recognition
High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-...
Publications
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418 publications
Impact of Particle Size and Polydispersity Index on the Clinical Applications of Lipidic Nanocarrier Systems
Lipid-based drug delivery systems, or lipidic carriers, are being extensively employed to enhance the bioavailability of poorly-soluble drugs. They have the ability to incorpora...
GhostNet: More Features From Cheap Operations
Deploying convolutional neural networks (CNNs) on embedded devices is difficult due to the limited memory and computation resources. The redundancy in feature maps is an importa...
INFOGEST static in vitro simulation of gastrointestinal food digestion
Developing a mechanistic understanding of the impact of food structure and composition on human health has increasingly involved simulating digestion in the upper gastrointestin...
First M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole
Abstract When surrounded by a transparent emission region, black holes are expected to reveal a dark shadow caused by gravitational light bending and photon capture at the event...
The diagnosis and management of non-alcoholic fatty liver disease: Practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association
These recommendations are based on the following: (1) a formal review and analysis of the recently published world literature on the topic [Medline search up to June 2011]; (2) ...
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a ...
Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis
Background The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with COVID-19 b...
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
Bounding box regression is the crucial step in object detection. In existing methods, while ℓn-norm loss is widely adopted for bounding box regression, it is not tailored to the...