Endless Forams: >34,000 Modern Planktonic Foraminiferal Images for Taxonomic Training and Automated Species Recognition Using Convolutional Neural Networks
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Endless Forams: >34,000 Modern Planktonic Foraminiferal Images for Taxonomic Training and Automated Species Recognition Using Convolutional Neural Networks
Authors
Keywords
-
Journal
Paleoceanography and Paleoclimatology
Volume -, Issue -, Pages -
Publisher
American Geophysical Union (AGU)
Online
2019-06-24
DOI
10.1029/2019pa003612
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance
- (2019) R. Mitra et al. MARINE MICROPALEONTOLOGY
- Systematic taxonomy of the Trilobatus sacculifer plexus and descendant Globigerinoidesella fistulosa (planktonic foraminifera)
- (2019) Christopher R. Poole et al. JOURNAL OF SYSTEMATIC PALAEONTOLOGY
- Distribution and ecology of the Globigerinoides ruber — Globigerinoides elongatus morphotypes in the Azores region during the late Pleistocene-Holocene
- (2018) Alessandro Bonfardeci et al. PALAEOGEOGRAPHY PALAEOCLIMATOLOGY PALAEOECOLOGY
- Species identification by conservation practitioners using online images: accuracy and agreement between experts
- (2018) Gail E. Austen et al. PeerJ
- Sixty-one thousand recent planktonic foraminifera from the Atlantic Ocean
- (2018) Leanne E. Elder et al. Scientific Data
- Evolutionary history biases inferences of ecology and environment from δ13C but not δ18O values
- (2017) Kirsty M. Edgar et al. Nature Communications
- Molecular and automated identification of the diatom genusFrustuliain northern Europe
- (2016) Pavla Urbánková et al. DIATOM RESEARCH
- Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains
- (2016) Ariadne Barbosa Gonçalves et al. PLoS One
- Species identification by experts and non-experts: comparing images from field guides
- (2016) G. E. Austen et al. Scientific Reports
- ImageNet Large Scale Visual Recognition Challenge
- (2015) Olga Russakovsky et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Inselect: Automating the Digitization of Natural History Collections
- (2015) Lawrence N. Hudson et al. PLoS One
- Attribute-Based Classification for Zero-Shot Visual Object Categorization
- (2013) Christoph H. Lampert et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Planktonic foraminifera stable isotopes and water column structure: Disentangling ecological signals
- (2013) Heather Birch et al. MARINE MICROPALEONTOLOGY
- The cryptic and the apparent reversed: lack of genetic differentiation within the morphologically diverse plexus of the planktonic foraminifer Globigerinoides sacculifer
- (2013) Aurore André et al. PALEOBIOLOGY
- A phylogeny of Cenozoic macroperforate planktonic foraminifera from fossil data
- (2011) Tracy Aze et al. BIOLOGICAL REVIEWS
- Virtual reflected-light microscopy
- (2011) A.P. HARRISON et al. JOURNAL OF MICROSCOPY
- Sensitivity of coccolithophores to carbonate chemistry and ocean acidification
- (2011) L. Beaufort et al. NATURE
- Learning from Imbalanced Data
- (2009) Haibo He et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- Feasibility of computer-aided identification of foraminiferal tests
- (2009) Kamal Ranaweera et al. MARINE MICROPALEONTOLOGY
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started