A novel semi-supervised framework combining contrastive learning with hierarchical probabilistic graphical models for remote sensing with limited labeled data. Our approach enhances CRFNet by learning ...

To address these issues, we propose a method based on conditional random field with spatio-temporal feature embedding under entropy constraints (CRF-STEEC). This method standardizes both trajectory ...

In this work, a novel hybridization of the multi-scale features extraction, multi-pathway 3D convolutional neural network (CNN), and Conditional Random Field (CRF) is employed for an automated MS ...

sdmTMB is an R package that fits spatial and spatiotemporal GLMMs (Generalized Linear Mixed Effects Models) using Template Model Builder (TMB), R-INLA, and Gaussian Markov random fields. One common ...