Zobrazeno 1 - 10
of 64
pro vyhledávání: '"JOHNSON, FAITH"'
Visual navigation takes inspiration from humans, who navigate in previously unseen environments using vision without detailed environment maps. Inspired by this, we introduce a novel no-RL, no-graph, no-odometry approach to visual navigation using fe
Externí odkaz:
http://arxiv.org/abs/2411.09893
Map representation learned by expert demonstrations has shown promising research value. However, recent advancements in the visual navigation field face challenges due to the lack of human datasets in the real world for efficient supervised represent
Externí odkaz:
http://arxiv.org/abs/2402.14281
Visual navigation follows the intuition that humans can navigate without detailed maps. A common approach is interactive exploration while building a topological graph with images at nodes that can be used for planning. Recent variations learn from p
Externí odkaz:
http://arxiv.org/abs/2402.12498
Autor:
Johnson, Faith, Dana, Kristin
In this work, we explore the use of hierarchical reinforcement learning (HRL) for the task of temporal sequence prediction. Using a combination of deep learning and HRL, we develop a stock agent to predict temporal price sequences from historical sto
Externí odkaz:
http://arxiv.org/abs/2310.05695
Agricultural domains are being transformed by recent advances in AI and computer vision that support quantitative visual evaluation. Using drone imaging, we develop a framework for characterizing the ripening process of cranberry crops. Our method co
Externí odkaz:
http://arxiv.org/abs/2309.00028
Autor:
Johnson, Faith, Dana, Kristin
Understanding pedestrian behavior patterns is a key component to building autonomous agents that can navigate among humans. We seek a learned dictionary of pedestrian behavior to obtain a semantic description of pedestrian trajectories. Supervised me
Externí odkaz:
http://arxiv.org/abs/2212.01426
Autor:
Johnson, Faith, Dana, Kristin
Publikováno v:
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 1002-1003. 2020
We consider the challenge of automated steering angle prediction for self driving cars using egocentric road images. In this work, we explore the use of feudal networks, used in hierarchical reinforcement learning (HRL), to devise a vehicle agent to
Externí odkaz:
http://arxiv.org/abs/2006.06869
Autor:
Johnson, Faith, Erasmus, C. J.
Publikováno v:
British Journal of Special Education; Sep2024, Vol. 51 Issue 3, p296-316, 21p
Autor:
Johnson, Faith Michelle
Thesis (M.S.)--University of Tennessee, Knoxville, 2004.
Title from title page screen (viewed Sept. 20, 2004). Thesis advisor: David A. Golden. Document formatted into pages (viii, 61 p. : ill. (some col.)). Vita. Includes bibliographical refere
Title from title page screen (viewed Sept. 20, 2004). Thesis advisor: David A. Golden. Document formatted into pages (viii, 61 p. : ill. (some col.)). Vita. Includes bibliographical refere
Externí odkaz:
http://etd.utk.edu/2004/JohnsonFaith.pdf
Autor:
BARNES, ADAM, CROOKES, DAVID, FREEMAN, WILL, GERLI, DAMIANO, JOHNSON, FAITH, JONES, DARRAN, KAUTZ, PAUL, MASON, GRAEME, MILNE, RORY, THORPE, NICK
Publikováno v:
Retro Gamer; 2024, Issue 257, p18-47, 30p, 59 Color Photographs