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Seishi Ninomiya
Seishi Ninomiya
Verified email at g.ecc.u-tokyo.ac.jp
Title
Cited by
Cited by
Year
On plant detection of intact tomato fruits using image analysis and machine learning methods
K Yamamoto, W Guo, Y Yoshioka, S Ninomiya
Sensors 14 (7), 12191-12206, 2014
3422014
Illumination invariant segmentation of vegetation for time series wheat images based on decision tree model
W Guo, UK Rage, S Ninomiya
Computers and electronics in agriculture 96, 58-66, 2013
2452013
A weakly supervised deep learning framework for sorghum head detection and counting
S Ghosal, B Zheng, SC Chapman, AB Potgieter, DR Jordan, X Wang, ...
Plant Phenomics, 2019
2322019
An informative linkage map of soybean reveals QTLs for flowering time, leaflet morphology and regions of segregation distortion
N Yamanaka, S Ninomiya, M Hoshi, Y Tsubokura, M Yano, Y Nagamura, ...
DNA research 8 (2), 61-72, 2001
2242001
Analysis of Petal Shape Variation of Primula sieboldii by Elliptic Fourier Descriptors and Principal Component Analysis
Y Yoshioka, H Iwata, RYO Ohsawa, S Ninomiya
Annals of Botany 94 (5), 657-664, 2004
1822004
Quantitative evaluation of soybean (Glycine max L. Merr.) leaflet shape by principal component scores based on elliptic Fourier descriptor
N Furuta, S Ninomiya, N Takahashi, H Ohmori, U Yasuo
Japanese Journal of Breeding 45 (3), 315-320, 1995
1621995
Automated characterization of flowering dynamics in rice using field-acquired time-series RGB images
W Guo, T Fukatsu, S Ninomiya
Plant methods 11 (1), 7, 2015
1612015
AntMap: constructing genetic linkage maps using an ant colony optimization algorithm
H Iwata, S Ninomiya
Breeding science 56 (4), 371-377, 2006
1532006
Comparison of ground cover estimates from experiment plots in cotton, sorghum and sugarcane based on images and ortho-mosaics captured by UAV
T Duan, B Zheng, W Guo, S Ninomiya, Y Guo, SC Chapman
Functional Plant Biology 44 (1), 169-183, 2016
1402016
Intact detection of highly occluded immature tomatoes on plants using deep learning techniques
Y Mu, TS Chen, S Ninomiya, W Guo
Sensors 20 (10), 2984, 2020
1282020
Chalkiness in rice: potential for evaluation with image analysis
Y Yoshioka, H Iwata, M Tabata, S Ninomiya, R Ohsawa
Crop Science 47 (5), 2113-2120, 2007
1282007
Automatic estimation of heading date of paddy rice using deep learning
SV Desai, VN Balasubramanian, T Fukatsu, S Ninomiya, W Guo
Plant Methods 15 (1), 76, 2019
1152019
Aerial imagery analysis–quantifying appearance and number of sorghum heads for applications in breeding and agronomy
W Guo, B Zheng, AB Potgieter, J Diot, K Watanabe, K Noshita, DR Jordan, ...
Frontiers in plant science 9, 1544, 2018
1062018
Data mining and wireless sensor network for agriculture pest/disease predictions
AK Tripathy, J Adinarayana, D Sudharsan, SN Merchant, UB Desai, ...
2011 World Congress on Information and Communication Technologies, 1229-1234, 2011
982011
Diallel analysis of leaf shape variations of citrus varieties based on elliptic Fourier descriptors
H Iwata, H Nesumi, S Ninomiya, Y Takano, Y Ukai
Breeding Science 52 (2), 89-94, 2002
962002
Characterization of peach tree crown by using high-resolution images from an unmanned aerial vehicle
Y Mu, Y Fujii, D Takata, B Zheng, K Noshita, K Honda, S Ninomiya, W Guo
Horticulture research 5, 2018
912018
EasyPCC: benchmark datasets and tools for high-throughput measurement of the plant canopy coverage ratio under field conditions
W Guo, B Zheng, T Duan, T Fukatsu, S Chapman, S Ninomiya
Sensors 17 (4), 798, 2017
912017
Providing agricultural models with mediated access to heterogeneous weather databases
MR Laurenson, T Kiura, S Ninomiya
Applied Engineering in Agriculture 18 (5), 617, 2002
832002
High-throughput field crop phenotyping: current status and challenges
S Ninomiya
Breeding Science 72 (1), 3-18, 2022
772022
Active learning with point supervision for cost-effective panicle detection in cereal crops
AL Chandra, SV Desai, VN Balasubramanian, S Ninomiya, W Guo
Plant Methods 16 (1), 34, 2020
762020
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Articles 1–20