引用次数
引用: 5,719
H-指数: 38
I10-指数 : 80
出版物: 243
Velocity Performance Indexes for Parallel Mechanisms with Actuation Redundancy
Clément M Gosselin , Imme Ebert-Uphoff
Proposal for a Self-Developing Practical course in Parallel Mechanisms
Clément M Gosselin , Imme Ebert-Uphoff
On some properties of POLMAN-3L parallel manipulator to the use as a 3-D measuring system for industrial/educational applications.
Clément M Gosselin , Imme Ebert-Uphoff
Architecture Independent Workspace Analysis of Planar Three-Legged Manipulators
Clément M Gosselin , Imme Ebert-Uphoff
Planar Point & Line Transformation with Blaschke-Grunwald Image Space Coordinates
Clement M Gosselin , Imme Ebert-Uphoff
Redundancy Resolution Schemes for Parallel Manipulators with Force Redundancy
Clement M Gosselin , Imme Ebert-Uphoff
Design of Cable-Suspended Planar Parallel Robots for an Optimal Workspace
Clément M Gosselin , Imme Ebert-Uphoff
WORKSPACE ANALYSIS OF A SIX DOF WIRE-DRIVEN PARALLEL MANIPULATOR
Clément M Gosselin , Imme Ebert-Uphoff
Some considerations regarding Statically Balanced Parallel Mechanisms (SBPM's)
Clément M Gosselin , Imme Ebert-Uphoff
Artificial Intelligence Applications in the Geosciences: Promises and Challenges for the Future I
Suzanne A Pierce , Tarka Wilcox , Imme Ebert-Uphoff , Renzhi Cao
AGU Fall Meeting 2018
2018
A primer on topological data analysis to support image analysis tasks in environmental science
Lander Ver Hoef , Henry Adams , Emily J King , Imme Ebert-Uphoff
Artificial Intelligence for the Earth Systems 2 ( 1) e220039 -e220039
14
2023
Exploring Texture Analysis to Aid Classification of Meteorological Phenomena in Satellite Imagery
Kristina Moen , Nathan J Mitchell , Yoonjin Lee , Lander Ver Hoef
104th AMS Annual Meeting
2024
Comparing Rotationally Invariant CNNs with Classical CNNs on Storm Forecast Data
Lander Ver Hoef , David John Gagne , Emily J King , Imme Ebert-Uphoff
103rd AMS Annual Meeting
2023
Leveraging spatiotemporal information in meteorological image sequences: From feature engineering to neural networks
Akansha S Bansal , Yoonjin Lee , Kyle Hilburn , Imme Ebert-Uphoff
Environmental Data Science 2 e31 -e31
1
2023
Artificial Intelligence for Low-Level Moisture from GOES-R Series
Akansha Singh Bansal , Kyle A Hilburn , Imme Ebert-Uphoff
103rd AMS Annual Meeting
2023
A Primer on Neural Network Architectures to Extract Information from Meteorological Image Sequences
Akansha Singh Bansal , Yoonjin Lee , Kyle A Hilburn , Imme Ebert-Uphoff
103rd AMS Annual Meeting
2023
Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School
Amy McGovern , David John Gagne , Christopher D Wirz , Imme Ebert-Uphoff
Bulletin of the American Meteorological Society
2023
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience
Antonios Mamalakis , Elizabeth A Barnes , Imme Ebert-Uphoff ,
Artificial Intelligence for the Earth Systems 1 ( 4) e220012 -e220012
70
2022
Explainable artificial intelligence in meteorology and climate science: Model fine-tuning, calibrating trust and learning new science
Antonios Mamalakis , Imme Ebert-Uphoff , Elizabeth A Barnes
Springer International Publishing 315 -339
31
2020
Carefully choose the baseline: Lessons learned from applying XAI attribution methods for regression tasks in geoscience
Antonios Mamalakis , Elizabeth A Barnes , Imme Ebert-Uphoff
Artificial Intelligence for the Earth Systems 2 ( 1) e220058 -e220058
24
2023