158 related articles for article (PubMed ID: 32849691)
1. A New Method for Counting Reproductive Structures in Digitized Herbarium Specimens Using Mask R-CNN.
Davis CC; Champ J; Park DS; Breckheimer I; Lyra GM; Xie J; Joly A; Tarapore D; Ellison AM; Bonnet P
Front Plant Sci; 2020; 11():1129. PubMed ID: 32849691
[TBL] [Abstract][Full Text] [Related]
2. A new fine-grained method for automated visual analysis of herbarium specimens: A case study for phenological data extraction.
Goëau H; Mora-Fallas A; Champ J; Love NLR; Mazer SJ; Mata-Montero E; Joly A; Bonnet P
Appl Plant Sci; 2020 Jun; 8(6):e11368. PubMed ID: 32626610
[TBL] [Abstract][Full Text] [Related]
3. Machine Learning Undercounts Reproductive Organs on Herbarium Specimens but Accurately Derives Their Quantitative Phenological Status: A Case Study of
Love NLR; Bonnet P; Goëau H; Joly A; Mazer SJ
Plants (Basel); 2021 Nov; 10(11):. PubMed ID: 34834835
[TBL] [Abstract][Full Text] [Related]
4. CrowdCurio: an online crowdsourcing platform to facilitate climate change studies using herbarium specimens.
Willis CG; Law E; Williams AC; Franzone BF; Bernardos R; Bruno L; Hopkins C; Schorn C; Weber E; Park DS; Davis CC
New Phytol; 2017 Jul; 215(1):479-488. PubMed ID: 28394023
[TBL] [Abstract][Full Text] [Related]
5. Herbarium records are reliable sources of phenological change driven by climate and provide novel insights into species' phenological cueing mechanisms.
Davis CC; Willis CG; Connolly B; Kelly C; Ellison AM
Am J Bot; 2015 Oct; 102(10):1599-609. PubMed ID: 26451038
[TBL] [Abstract][Full Text] [Related]
6. A new method and insights for estimating phenological events from herbarium specimens.
Pearson KD
Appl Plant Sci; 2019 Mar; 7(3):e01224. PubMed ID: 30937217
[TBL] [Abstract][Full Text] [Related]
7. Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States.
Park DS; Breckheimer I; Williams AC; Law E; Ellison AM; Davis CC
Philos Trans R Soc Lond B Biol Sci; 2018 Nov; 374(1763):. PubMed ID: 30455212
[TBL] [Abstract][Full Text] [Related]
8. Old Plants, New Tricks: Phenological Research Using Herbarium Specimens.
Willis CG; Ellwood ER; Primack RB; Davis CC; Pearson KD; Gallinat AS; Yost JM; Nelson G; Mazer SJ; Rossington NL; Sparks TH; Soltis PS
Trends Ecol Evol; 2017 Jul; 32(7):531-546. PubMed ID: 28465044
[TBL] [Abstract][Full Text] [Related]
9. Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research.
Pearson KD; Nelson G; Aronson MFJ; Bonnet P; Brenskelle L; Davis CC; Denny EG; Ellwood ER; Goëau H; Heberling JM; Joly A; Lorieul T; Mazer SJ; Meineke EK; Stucky BJ; Sweeney P; White AE; Soltis PS
Bioscience; 2020 Jul; 70(6):610-620. PubMed ID: 32665738
[TBL] [Abstract][Full Text] [Related]
10. Herbarium specimens can reveal impacts of climate change on plant phenology; a review of methods and applications.
Jones CA; Daehler CC
PeerJ; 2018; 6():e4576. PubMed ID: 29632745
[TBL] [Abstract][Full Text] [Related]
11. Toward a large-scale and deep phenological stage annotation of herbarium specimens: Case studies from temperate, tropical, and equatorial floras.
Lorieul T; Pearson KD; Ellwood ER; Goëau H; Molino JF; Sweeney PW; Yost JM; Sachs J; Mata-Montero E; Nelson G; Soltis PS; Bonnet P; Joly A
Appl Plant Sci; 2019 Mar; 7(3):e01233. PubMed ID: 30937225
[TBL] [Abstract][Full Text] [Related]
12. A new phenological metric for use in pheno-climatic models: A case study using herbarium specimens of
Love NLR; Park IW; Mazer SJ
Appl Plant Sci; 2019 Jul; 7(7):e11276. PubMed ID: 31346508
[TBL] [Abstract][Full Text] [Related]
13. Analyzing trait-climate relationships within and among taxa using machine learning and herbarium specimens.
Wilde BC; Bragg JG; Cornwell W
Am J Bot; 2023 May; 110(5):e16167. PubMed ID: 37043678
[TBL] [Abstract][Full Text] [Related]
14. Digitization protocol for scoring reproductive phenology from herbarium specimens of seed plants.
Yost JM; Sweeney PW; Gilbert E; Nelson G; Guralnick R; Gallinat AS; Ellwood ER; Rossington N; Willis CG; Blum SD; Walls RL; Haston EM; Denslow MW; Zohner CM; Morris AB; Stucky BJ; Carter JR; Baxter DG; Bolmgren K; Denny EG; Dean E; Pearson KD; Davis CC; Mishler BD; Soltis PS; Mazer SJ
Appl Plant Sci; 2018 Feb; 6(2):e1022. PubMed ID: 29732253
[TBL] [Abstract][Full Text] [Related]
15. Automated Extraction of Phenotypic Leaf Traits of Individual Intact Herbarium Leaves from Herbarium Specimen Images Using Deep Learning Based Semantic Segmentation.
Hussein BR; Malik OA; Ong WH; Slik JWF
Sensors (Basel); 2021 Jul; 21(13):. PubMed ID: 34283110
[TBL] [Abstract][Full Text] [Related]
16. The phenology of Rubus fruticosus in Ireland: herbarium specimens provide evidence for the response of phenophases to temperature, with implications for climate warming.
Diskin E; Proctor H; Jebb M; Sparks T; Donnelly A
Int J Biometeorol; 2012 Nov; 56(6):1103-11. PubMed ID: 22382508
[TBL] [Abstract][Full Text] [Related]
17. Using Convolutional Neural Networks to Efficiently Extract Immense Phenological Data From Community Science Images.
Reeb RA; Aziz N; Lapp SM; Kitzes J; Heberling JM; Kuebbing SE
Front Plant Sci; 2021; 12():787407. PubMed ID: 35111176
[TBL] [Abstract][Full Text] [Related]
18. Generating segmentation masks of herbarium specimens and a data set for training segmentation models using deep learning.
White AE; Dikow RB; Baugh M; Jenkins A; Frandsen PB
Appl Plant Sci; 2020 Jun; 8(6):e11352. PubMed ID: 32626607
[TBL] [Abstract][Full Text] [Related]
19. Overlooked climate parameters best predict flowering onset: Assessing phenological models using the elastic net.
Park IW; Mazer SJ
Glob Chang Biol; 2018 Dec; 24(12):5972-5984. PubMed ID: 30218548
[TBL] [Abstract][Full Text] [Related]
20. Maximizing human effort for analyzing scientific images: A case study using digitized herbarium sheets.
Brenskelle L; Guralnick RP; Denslow M; Stucky BJ
Appl Plant Sci; 2020 Jun; 8(6):e11370. PubMed ID: 32626612
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
