Deep Learning Segmentation of Satellite Imagery Identifies Aquatic Vegetation Associated with Snail Intermediate Hosts of Schistosomiasis in Senegal, Africa.
Zac Yung-Chun LiuAndrew J. ChamberlinKrti TallamIsabel J. JonesLance L. LamoreJohn BauerMariano BrescianiCaitlin M. WolfeRenato CasagrandiLorenzo MariMarino GattoAbdou Kâ DiongueAmadou Lamine ToureJason R. RohrGilles RiveauNicolas JouanardChelsea L. WoodSusanne H. SokolowLisa MandleGretchen DailyEric F. LambinGiulio A. De LeoPublished in: Remote. Sens. (2022)
Keyphrases
- deep learning
- satellite imagery
- remote sensing
- satellite images
- land cover
- change detection
- urban areas
- image analysis
- image segmentation
- remote sensing images
- level set
- unsupervised learning
- multispectral
- machine learning
- segmentation method
- unsupervised feature learning
- segmentation algorithm
- object segmentation
- mental models
- high resolution
- image processing
- multiscale
- hyperspectral
- probabilistic model
- weakly supervised
- object detection
- pattern recognition