Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Zachary D. Siegel"'
Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning.
Autor:
Naihui Zhou, Zachary D Siegel, Scott Zarecor, Nigel Lee, Darwin A Campbell, Carson M Andorf, Dan Nettleton, Carolyn J Lawrence-Dill, Baskar Ganapathysubramanian, Jonathan W Kelly, Iddo Friedberg
Publikováno v:
PLoS Computational Biology, Vol 14, Iss 7, p e1006337 (2018)
The accuracy of machine learning tasks critically depends on high quality ground truth data. Therefore, in many cases, producing good ground truth data typically involves trained professionals; however, this can be costly in time, effort, and money.
Externí odkaz:
https://doaj.org/article/ad87ca982fb54245825798da5a52f6ce
Publikováno v:
Teaching of Psychology. 48:90-94
In this article, we discuss the ways in which psychology educators can assist students who have color vision deficiency (CVD). We outline basic information concerning CVD, offer tips for instructors to help students with CVD access content materials
Publikováno v:
Journal of Experimental Psychology: Human Perception and Performance. 43:1805-1814
Research over the past 20 years has consistently shown that egocentric distance is underperceived in virtual environments (VEs) compared with real environments. In 2 experiments, judgments of object distance (Experiment 1) and object size (Experiment
Publikováno v:
ACM Transactions on Applied Perception. 15:1-16
Underperception of egocentric distance in virtual reality has been a persistent concern for almost 20 years. Modern head-mounted displays (HMDs) appear to have begun to ameliorate underperception. The current study examined several aspects of perceiv
Autor:
Nigel Lee, Jonathan W. Kelly, Zachary D. Siegel, Carson M. Andorf, Dan Nettleton, Scott Zarecor, Iddo Friedberg, Baskar Ganapathysubramanian, Darwin A. Campbell, Naihui Zhou, Carolyn J. Lawrence-Dill
Publikováno v:
PLoS Computational Biology
PLoS Computational Biology, Vol 14, Iss 7, p e1006337 (2018)
PLoS Computational Biology, Vol 14, Iss 7, p e1006337 (2018)
The accuracy of machine learning tasks critically depends on high quality ground truth data. Therefore, in many cases, producing good ground truth data typically involves trained professionals; however, this can be costly in time, effort, and money.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4df9e58cf45cb14ed8a7d747a48feb3e
https://doi.org/10.1101/265918
https://doi.org/10.1101/265918
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 20:588-595
Distance in immersive virtual reality is commonly underperceived relative to intended distance, causing virtual environments to appear smaller than they actually are. However, a brief period of interaction by walking through the virtual environment w
Autor:
Jonathan W. Kelly, Zachary D. Siegel
Publikováno v:
Attention, perceptionpsychophysics. 79(1)
Distances tend to be underperceived in virtual environments (VEs) by up to 50%, whereas distances tend to be perceived accurately in the real world. Previous work has shown that allowing participants to interact with the VE while receiving continual
Publikováno v:
Attention, perceptionpsychophysics. 77(6)
Distance is commonly underperceived by up to 50 % in virtual environments (VEs), in contrast to relatively accurate real world judgments. Experiments reported by Geuss, Stefanucci, Creem-Regehr, and Thompson (Journal of Experimental Psychology: Human
Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning.
Autor:
Zhou, Naihui1,2, Siegel, Zachary D.3, Zarecor, Scott4, Lee, Nigel5, Campbell, Darwin A.4, Andorf, Carson M.6,7, Nettleton, Dan1,8, Lawrence-Dill, Carolyn J.1,4,9, Ganapathysubramanian, Baskar5, Kelly, Jonathan W.3 jonkelly@iastate.edu, Friedberg, Iddo1,2 idoerg@iastate.edu
Publikováno v:
PLoS Computational Biology. 7/30/2018, Vol. 14 Issue 7, p1-16. 16p. 2 Color Photographs, 1 Diagram, 2 Charts, 3 Graphs.