Arti Singh
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Machine learning for high throughput stress phenotyping in plants
A Singh, B Ganapathysubramanian, AK Singh, S Sarkar
Trends in plant science 21 (2), 110–124, 2016
Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives
Singh, A.K., Ganapathysubramanian, B., Sarkar, S. and Singh, A.
Trends in Plant Science., 2018
An explainable deep machine vision framework for plant stress phenotyping
S Ghosal, D Blystone, AK Singh, B Ganapathysubramanian, A Singh, ...
Proceedings of the National Academy of Sciences 115 (18), 4613-4618, 2018
Plant disease identification using explainable 3D deep learning on hyperspectral images
K Nagasubramanian, S Jones, AK Singh, S Sarkar, A Singh, ...
Plant Methods 15 (1), 1-10, 2019
Ntire 2018 challenge on spectral reconstruction from rgb images
B Arad, O Ben-Shahar, R Timofte, L Van Gool, L Zhang, MH Yang, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
A real-time phenotyping framework using machine learning for plant stress severity rating in soybean
HS Naik, J Zhang, A Lofquist, T Assefa, S Sarkar, D Ackerman, A Singh, ...
Plant methods 13 (1), 23, 2017
Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems
K Nagasubramanian, S Jones, S Sarkar, AK Singh, A Singh, ...
Plant Methods 14 (1), 86, 2018
A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting
G Sambuddha, Z Bangyou, CC Scott, PB Andries, JR David, W Xuemin, ...
Plant Phenomics, 2019
Challenges and Opportunities in Machine-Augmented Plant Stress Phenotyping
A Singh, S Jones, B Ganapathysubramanian, S Sarkar, D Mueller, ...
Trends in Plant Science, 2021
A deep learning framework to discern and count microscopic nematode eggs
A Akintayo, GL Tylka, AK Singh, B Ganapathysubramanian, A Singh, ...
Scientific Reports 8 (1), 9145, 2018
Computer vision and machine learning for robust phenotyping in genome-wide studies
J Zhang, HS Naik, T Assefa, S Sarkar, RVC Reddy, A Singh, ...
Scientific reports 7, 44048, 2017
Genome-wide association and epistasis studies unravel the genetic architecture of sudden death syndrome resistance in soybean
Jiaoping Zhang , Arti Singh, Daren Shane Mueller and Asheesh Kumar Singh
The Plant Journal, 2015
Computer vision and machine learning enabled soybean root phenotyping pipeline
KG Falk, TZ Jubery, SV Mirnezami, KA Parmley, S Sarkar, A Singh, ...
Plant Methods 16 (1), 5, 2020
Genetic architecture of Charcoal Rot (Macrophomina phaseolina) Resistance in Soybean revealed using a diverse panel
SM Coser, RV Chowda Reddy, J Zhang, DS Mueller, A Mengistu, ...
Frontiers in plant science 8, 1626, 2017
Allelic variation at Psy1-A1 and association with yellow pigment in durum wheat grain
A Singh, S Reimer, CJ Pozniak, FR Clarke, JM Clarke, RE Knox, ...
Theoretical and Applied Genetics 118 (8), 1539-1548, 2009
Raffinose family oligosaccharides: friend or foe for human and plant health?
D Elango, K Rajendran, L Van der Laan, S Sebastiar, J Raigne, ...
Frontiers in Plant Science, 304, 2022
UAS-Based Plant Phenotyping for Research and Breeding Applications
W Guo, ME Carroll, A Singh, TL Swetnam, N Merchant, S Sarkar, ...
Plant Phenomics 2021, 2021
Identification and mapping of leaf, stem and stripe rust resistance quantitative trait loci and their interactions in durum wheat
A Singh, MP Pandey, AK Singh, RE Knox, K Ammar, JM Clarke, ...
Molecular breeding 31 (2), 405-418, 2013
Identification and mapping in spring wheat of genetic factors controlling stem rust resistance and the study of their epistatic interactions across multiple environments
A Singh, RE Knox, RM DePauw, AK Singh, RD Cuthbert, HL Campbell, ...
Theoretical and Applied Genetics 126 (8), 1951-1964, 2013
Main and epistatic loci studies in soybean for Sclerotinia sclerotiorum resistance reveal multiple modes of resistance in multi-environments
TC Moellers, A Singh, J Zhang, J Brungardt, M Kabbage, DS Mueller, ...
Scientific reports 7 (1), 3554, 2017
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Articles 1–20