bayesImageS

Various algorithms for segmentation of 2D and 3D images, such as computed tomography and satellite remote sensing. This package implements Bayesian image analysis using the hidden Potts model with external field prior of Moores et al. (2015) doi:10.1016/j.csda.2014.12.001. Latent labels are sampled using chequerboard updating or Swendsen-Wang. Algorithms for the smoothing parameter include pseudolikelihood, path sampling, the exchange algorithm, approximate Bayesian computation (ABC-MCMC and ABC-SMC), and the parametric functional approximate Bayesian (PFAB) algorithm. Refer to doi:10.1007/978-3-030-42553-1_6 for an overview and also to doi:10.1007/s11222-014-9525-6 and doi:10.1214/18-BA1130 for further details of specific algorithms.

Last 30 days

This package has been downloaded 759 times in the last 30 days. More downloads than an obscure whitepaper, but not enough to bring down any servers. A solid effort! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 67 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 10,739 times in the last 365 days. The downloads are officially high enough to crash an underfunded departmental server. Quite an accomplishment! The day with the most downloads was Sep 11, 2024 with 92 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.