Tennyson S Jellins, Tyler L Borko, RayLee Otero-Bell, Kelly Arnett, Scott Saunders, Sharon N Poisson, Karen D Orjuela, Setareh Salehi Omran, William J Jones, Michelle Leppert, Ashley Madera, Aaron Carlson, Daniel M Pastula, Brian M Sauer, Amanda L Piquet, Nicole R Gonzales
Diversity, equity, and inclusion (DEI) in medical education: DEI at the bedside
Journal of the neurological sciences
wildfires uncontrolled fires fuelled dry conditions high winds flammable materials profoundly impact vegetation leading significant consequences including noteworthy changes ecosystems study provide novel methodology understand evaluate postfire effects vegetation regions affected wildfires earthobservation data various satellite sources vital monitoring vegetation assessing impact effects understood detecting vegetation change years using novel unsupervised method termed deep embedded clustering dec enables us classify regions based whether change vegetation fire model achieves impressive accuracy 9617 appropriate vegetation indices used evaluate evolution vegetation patterns years study utilized enhanced vegetation index evi based trend analysis showing greening fraction ranges 01 224 km2 browning fraction ranges 01 181 km2 years vegetation recovery maps created assess revegetation regions affected fire performed via deep learningbased unsupervised method adaptive generative adversarial neural network model adaptigan postfire data collected various regions affected wildfire training error 0075 proving capability based results obtained study approach tends notable merits compared preexisting works