activity
20172021
most citedObstacle Avoidance through Deep Networks based Intermediate Perception

34 citations · 41 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2021★ 1 cited

SalienTrack: providing salient information for semi-automated self-tracking feedback with model explanations

Yunlong Wang, Jiaying Liu, Homin Park +4

Self-tracking can improve people's awareness of their unhealthy behaviors and support reflection to inform behavior change. Increasingly, new technologies make tracking easier, lea…

cs.RO2021★ 1 cited

Impact of Explanation on Trust of a Novel Mobile Robot

Stephanie Rosenthal, Elizabeth J. Carter

One challenge with introducing robots into novel environments is misalignment between supervisor expectations and reality, which can greatly affect a user's trust and continued use…

cs.LG2018★ 4 cited

Understanding Convolutional Networks with APPLE : Automatic Patch Pattern Labeling for Explanation

Sandeep Konam, Ian Quah, Stephanie Rosenthal +1

With the success of deep learning, recent efforts have been focused on analyzing how learned networks make their classifications. We are interested in analyzing the network output…

cs.RO2017★ 1 cited

UAV and Service Robot Coordination for Indoor Object Search Tasks

Sandeep Konam, Stephanie Rosenthal, Manuela Veloso

Our CoBot robots have successfully performed a variety of service tasks in our multi-building environment including accompanying people to meetings and delivering objects to office…

cs.RO2017★ 34 cited

Obstacle Avoidance through Deep Networks based Intermediate Perception

Shichao Yang, Sandeep Konam, Chen Ma +3

Obstacle avoidance from monocular images is a challenging problem for robots. Though multi-view structure-from-motion could build 3D maps, it is not robust in textureless environme…