Welte, T.
* 2014: Automated Characterization of Breast Lesions Imaged With an Ultrafast DCE-MR Protocol
Welter, J.
* 2012: Automating Mapping Production for The Enterprise: From Contract To Delivery
* 2012: Multi-sensor Approach To Semi-Global Matching, A
Weltin, U.[Uwe]
* 2012: Sparse stereo by edge-based search using dynamic programming
Welton, E.J.[Ellsworth J.]
* 2018: Vertically Resolved Precipitation Intensity Retrieved through a Synergy between the Ground-Based NASA MPLNET Lidar Network Measurements, Surface Disdrometer Datasets and an Analytical Model Solution
* 2019: Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET) Automatic Precipitation Detection Algorithm
* 2020: Determination of Lidar Ratio for Major Aerosol Types over Western North Pacific Based on Long-Term MPLNET Data
* 2022: Volcanic Eruption of Cumbre Vieja, La Palma, Spain: A First Insight to the Particulate Matter Injected in the Troposphere
Welty, R.
* 1991: RADIUS Common Development Environment, The
* 1992: RADIUS Common Development Environment, The
Welty, R.P.
* 1992: 3-D Model Alignment without Computing Pose
* 1993: Image Understanding Environment: Data Exchange, The
Weltzien, C.[Cornelia]
* 2019: Analyzing Temporal and Spatial Characteristics of Crop Parameters Using Sentinel-1 Backscatter Data
* 2020: Growth Height Determination of Tree Walls for Precise Monitoring in Apple Fruit Production Using UAV Photogrammetry
* 2021: Agricultural Monitoring Using Polarimetric Decomposition Parameters of Sentinel-1 Data
* 2021: Detecting Phenological Development of Winter Wheat and Winter Barley Using Time Series of Sentinel-1 and Sentinel-2
* 2022: Crop Monitoring Using Sentinel-2 and UAV Multispectral Imagery: A Comparison Case Study in Northeastern Germany
* 2022: UAV Oblique Imagery with an Adaptive Micro-Terrain Model for Estimation of Leaf Area Index and Height of Maize Canopy from 3D Point Clouds
Weltzin, J.F.[Jake F.]
* 2016: Mapping Presence and Predicting Phenological Status of Invasive Buffelgrass in Southern Arizona Using MODIS, Climate and Citizen Science Observation Data