activity
20182023
most citedEvaluation of state representation methods in robot hand-eye coordination learning from demonstration

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Cosmic Microwave Background Recovery: A Graph-Based Bayesian Convolutional Network Approach

Jadie Adams, Steven Lu, Krzysztof M. Gorski +2

The cosmic microwave background (CMB) is a significant source of knowledge about the origin and evolution of our universe. However, observations of the CMB are contaminated by fore…

cs.LG2021

Mars Image Content Classification: Three Years of NASA Deployment and Recent Advances

Kiri Wagstaff, Steven Lu, Emily Dunkel +8

The NASA Planetary Data System hosts millions of images acquired from the planet Mars. To help users quickly find images of interest, we have developed and deployed content-based c…

cs.CV2019

Bridging Visual Perception with Contextual Semantics for Understanding Robot Manipulation Tasks

Chen Jiang, Martin Jagersand

Understanding manipulation scenarios allows intelligent robots to plan for appropriate actions to complete a manipulation task successfully. It is essential for intelligent robots…

cs.RO2019★ 2 cited

Evaluation of state representation methods in robot hand-eye coordination learning from demonstration

Jun Jin, Masood Dehghan, Laura Petrich +2

We evaluate different state representation methods in robot hand-eye coordination learning on different aspects. Regarding state dimension reduction: we evaluates how these state r…

cs.CV2018

Video Object Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting

Mennatullah Siam, Chen Jiang, Steven Lu +4

Video object segmentation is an essential task in robot manipulation to facilitate grasping and learning affordances. Incremental learning is important for robotics in unstructured…