IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Graph matching (GM) has been a long-standing combinatorial problem due to its NP-hard nature. Recently (deep) learning-based approaches have shown their superiority over the traditional solvers while the methods are almost based on supervised learnin...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jun 23, 2023
Intra prediction is a crucial part of video compression, which utilizes local information in images to eliminate spatial redundancy. As the state-of-the-art video coding standard, Versatile Video Coding (H.266/VVC) employs multiple directional predic...
Wireless Sensor Networks (WSNs) have been adopted in various environmental pollution monitoring applications. As an important environmental field, water quality monitoring is a vital process to ensure the sustainable, important feeding of and as a li...
The problem of missing data, particularly for dichotomous variables, is a common issue in medical research. However, few studies have focused on the imputation methods of dichotomous data and their performance, as well as the applicability of these i...
Neural networks : the official journal of the International Neural Network Society
Jun 5, 2023
Although graph representation learning has been studied extensively in static graph settings, dynamic graphs are less investigated in this context. This paper proposes a novel integrated variational framework called DYnamic mixture Variational Graph ...
The last three years have been a game changer in the way medicine is practiced. The COVID-19 pandemic changed the obstetrics and gynecology scenery. Pregnancy complications, and even death, are preventable due to maternal-fetal monitoring. A fast and...
Neural networks : the official journal of the International Neural Network Society
May 10, 2023
Distance metric learning has been a promising technology to improve the performance of algorithms related to distance metrics. The existing distance metric learning methods are either based on the class center or the nearest neighbor relationship. In...
International journal of molecular sciences
May 6, 2023
Heterogeneous three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is an important but very challenging technique for recovering the conformational heterogeneity of flexible biological macromolecules such as pro...
BACKGROUND: Identifying patterns within ICU medication regimens may help artificial intelligence algorithms to better predict patient outcomes; however, machine learning methods incorporating medications require further development, including standar...
Cryo-electron microscopy (cryo-EM) is a widely used structural determination technique. Because of the extremely low signal-to-noise ratio (SNR) of images captured by cryo-EM, clustering single-particle cryo-EM images with high accuracy is challengin...