We present a sample-efficient image segmentation method using active learning, we call it Active Bayesian UNet, or AB-UNet. This is a convolutional neural network using batch normalization and max-pool dropout. The Bayesian setup is achieved by explo...
Accurate segmentation of cardiovascular structures plays an important role in many clinical applications. Recently, fully convolutional networks (FCNs), led by the UNet architecture, have significantly improved the accuracy and speed of semantic segm...
Photoacoustic (PA) imaging can provide both chemical and micro-architectural information for biological tissues. However, photoacoustic imaging for bone tissue remains a challenging topic due to complicated ultrasonic propagations in the porous bone....
Canopy gaps and their associated processes play an important role in shaping forest structure and dynamics. Understanding the information about canopy gaps allows forest managers to assess the potential for regeneration and plan interventions to enha...
The Yangtze River Basin, one of China’s most vital watersheds, sustains both ecological balance and human livelihoods through its extensive lake systems. However, since the 1980s, these lakes have experienced significant ecological degradation,...
Smoke, a byproduct of forest and grassland combustion, holds the key to precise and rapid identification—an essential breakthrough in early wildfire detection, critical for forest and grassland fire monitoring and early warning. To address the...