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David P. Hughes
Researcher at Pennsylvania State University
Publications - 190
Citations - 12379
David P. Hughes is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Ophiocordyceps & Ophiocordyceps unilateralis. The author has an hindex of 48, co-authored 184 publications receiving 9826 citations. Previous affiliations of David P. Hughes include University of Edinburgh & California State Polytechnic University, Pomona.
Papers
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Journal ArticleDOI
Using Deep Learning for Image-Based Plant Disease Detection
TL;DR: In this article, a deep convolutional neural network was used to identify 14 crop species and 26 diseases (or absence thereof) using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions.
Journal ArticleDOI
Unveiling Dust-enshrouded Star Formation in the Early Universe: a Sub-mm Survey of the Hubble Deep Field
David P. Hughes,Steve Serjeant,James Dunlop,Michael Rowan-Robinson,Andrew Blain,Robert G. Mann,Rob Ivison,John A. Peacock,Andreas Efstathiou,Walter Kieran Gear,Seb Oliver,Andy Lawrence,Malcolm S. Longair,P. Goldschmidt,Tim Jenness +14 more
TL;DR: In this paper, the authors presented the deepest sub-mm survey of the sky to date, taken with the SCUBA camera on the James Clerk Maxwell Telescope and centred on the Hubble Deep Field.
Posted Content
An open access repository of images on plant health to enable the development of mobile disease diagnostics
David P. Hughes,Marcel Salathé +1 more
TL;DR: These data are the beginning of an on-going, crowdsourcing effort to enable computer vision approaches to help solve the problem of yield losses in crop plants due to infectious diseases.
Journal ArticleDOI
Deep Learning for Image-Based Cassava Disease Detection
Amanda Ramcharan,Kelsee Baranowski,Peter McCloskey,Babuali Ahmed,James P. Legg,David P. Hughes +5 more
TL;DR: Using a dataset of cassava disease images taken in the field in Tanzania, transfer learning is applied to train a deep convolutional neural network to identify three diseases and two types of pest damage (or lack thereof).
Journal ArticleDOI
Deep radio imaging of the SCUBA 8-mJy survey fields: sub-mm source identifications and redshift distribution
Rob Ivison,Thomas R. Greve,Ian Smail,James Dunlop,Nathan Roche,S. E. Scott,Mat Page,Jamie Stevens,Omar Almaini,Andrew Blain,Chris J. Willott,M. Fox,David Gilbank,Steve Serjeant,David P. Hughes +14 more
TL;DR: The SCUBA 8mJy survey is the largest submm extragalactic mapping survey undertaken to date, centred on the Lockman Hole and ELAIS N2 regions as discussed by the authors.