An analysis of altitude, citizen science and a convolutional neural network feedback loop on object detection in Unmanned Aerial Systems
Authors:
- Connor BowleyCBConnor Bowley
- Marshall MattinglyMMMarshall Mattingly
- Andrew BarnasABAndrew Barnas
- Susan Ellis-FelegeSESusan Ellis-Felege
- Travis DesellTDTravis Desell
- 1 May 2019
- journal article
- conference paper
- Published by Elsevier in Journal of Computational Science
- Vol. 34, 102-116
Abstract
No abstract availableKeywords
Funding Information
- National Science Foundation
This publication has 18 references indexed in Scilit:
- ImageNet Large Scale Visual Recognition ChallengeInternational Journal of Computer Vision, 2015
- The Pascal Visual Object Classes Challenge: A RetrospectiveInternational Journal of Computer Vision, 2014
- eBird: Engaging Birders in Science and ConservationPLOS Biology, 2011
- Planet Hunters: the first two planet candidates identified by the public using the Kepler public archive data★Monthly Notices of the Royal Astronomical Society, 2011
- Using a Free Online Citizen-Science Project to Teach Observation & Quantification of Animal BehaviorThe American Biology Teacher, 2010
- Citizen Science: A Developing Tool for Expanding Science Knowledge and Scientific LiteracyBioScience, 2009
- Galaxy Zoo: morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey★Monthly Notices of the Royal Astronomical Society, 2008
- "GrabCut"ACM Transactions on Graphics, 2004
- The Sloan Digital Sky Survey: Technical SummaryThe Astronomical Journal, 2000
- Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)The Annals of Statistics, 2000