Arti Singh
Title
Cited by
Cited by
Year
Machine learning for high throughput stress phenotyping in plants
A Singh, B Ganapathysubramanian, A Kumar Singh, S Sarkar
Trends in plant science 21 (2), 110–124, 2016
3162016
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
1172018
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
952018
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
702009
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
642017
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
622015
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
562013
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
502013
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
402017
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
392018
Stripe rust and leaf rust resistance QTL mapping, epistatic interactions, and co-localization with stem rust resistance loci in spring wheat evaluated over three continents
A Singh, RE Knox, RM DePauw, AK Singh, RD Cuthbert, HL Campbell, ...
Theoretical and applied genetics 127 (11), 2465-2477, 2014
312014
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
292018
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
252017
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
24*2019
Disease and insect resistance in plants
DP Singh, A Singh
Science Publishers, 2005
242005
Genetic mapping of common bunt resistance and plant height QTL in wheat
A Singh, RE Knox, RM DePauw, AK Singh, RD Cuthbert, S Kumar, ...
Theoretical and applied genetics 129 (2), 243-256, 2016
232016
Genetics of pre-harvest sprouting resistance in a cross of Canadian adapted durum wheat genotypes
AK Singh, RE Knox, JM Clarke, FR Clarke, A Singh, RM DePauw, ...
Molecular breeding 33 (4), 919-929, 2014
232014
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
22*2018
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
212017
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
19*2019
The system can't perform the operation now. Try again later.
Articles 1–20