Journal Paper (before 2010)

Guo,W.*, Fukano,Y., Noshita, K., Ninomiya,S.(2020). Field-based individual plant phenotyping of herbaceous species by unmanned aerial vehicle. Ecology and Evolution. 2020; 00: 1– 9. https://doi.org/10.1002/ece3.6861

David,E., Madec,S., Sadeghi-Tehran, P., Aasen,H., Zheng,B., Liu,S., Kirchgessner, N., Ishikawa, G., Nagasawa, K., Badhon,M.A., Pozniak, C., Solan, B., Hund, A., Chapman, S.C., Baret, F., Stavness, I.*, Guo, W.*,(2020). Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods. Plant Phenomics, Volume 2020, Article ID 3521852, https://doi.org/10.34133/2020/3521852

Fukano,Y.*, Guo,W., Uchida1, K., Tachiki, Y.(2020).Contemporary adaptive divergence of plant competitive traits in urban and rural populations and its effect on weed management. Journal of Ecology. https://doi.org/10.1111/1365-2745.13472

Mu, Y.*, Chen,T., Ninomiya, S., Guo, W.* (2020) Intact detection of highly occluded immature tomatoes on plants using deep learning techniques. Sensors 2020, 20(10), 2984. https://doi.org/10.3390/s20102984

Chandra, A.L., Desai, S. V., Balasubramanian, V. N.*, Guo, W.* (2020) Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey. Journal of Advanced Computing and Communications. https://doi.org/10.34048/ACC.2020.1.F1

Chandra, A.L., Desai, S. V., Balasubramanian, V. N.*, Ninomiya, S., Guo, W.* (2020). Active learning with point supervision for cost-effective panicle detection in cereal crops. Plant Methods 16, 34. https://doi.org/10.1186/s13007-020-00575-8

Desai, S. V., Lagandula, A. C., Guo, W., Ninomiya, S., & Balasubramanian, V. N.* (2019). An Adaptive Supervision Framework for Active Learning in Object Detection. 30th British Machine Vision Conference (BMVC). 9th—12th September 2019, Cardiff University, England. https://bmvc2019.org/authors/accepted-papers-2/

Tresch, L., Mu,Y., Itoh,A., Kaga,A., Taguchi,K., Hirafuji,M., Ninomiya,S., Guo, W.*(2019), Easy MPE: Extraction of Quality Microplot Images for UAV-Based High-Throughput Field Phenotyping. Plant Phenomics, vol. 2019, Article ID 2591849, 9 pages, 2019. https://doi.org/10.34133/2019/2591849

Desai, S., Balasubramanian, V., Fukatsu, T., Ninomiya, S., Guo, W.*(2019). Automatic estimation of heading date of paddy rice using deep learning. Plant Methods, 15(1), 76. https://doi.org/10.1186/s13007-019-0457-1

Ghosal,S., Zheng, B., Chapman, S.C., Potgieter, A.B., Jordan,D.R., Wang,X., Singh, A.K., Singh, A., Hirafuji, M., Ninomiya, S., Ganapathysubramanian, B., Sarkar, S.*, Guo, W.*(2019). A weakly supervised deep learning framework for sorghum head detection and counting. Plant Phenomics, vol. 2019, Article ID 1525874, 14 pages, 2019. https://doi.org/10.34133/2019/1525874

Hu P., Guo, W., Chapman, S.C., Guo, Y., Zheng, B.*(2019). Pixel size of aerial imagery constrains the applications of unmanned aerial vehicle in crop breeding. ISPRS Journal of Photogrammetry and Remote Sensing, 154, 1–9. https://doi.org/10.1016/j.isprsjprs.2019.05.008

Guo, W., Iwata, H.*(2018) Genomic selection and high-throughput phenotyping to increase the efficiency and speed of crop breeding. ). The Japanese Society of Photosynthesis Research.28 (3), 180-193 (In Japanese)

Ito, A., Guo, W., Taguchi, K., Hirafuji, M., (2018). Development of data distribution and time-series browsing method of drone aerial image using IIIF. Agriculture Information Research.
https://doi.org/10.3173/air.27.28 (In Japanese)

Mu, Y., Fujii, Y., Takata, D., Zheng, B., Noshita, K., Honda, K., Ninomiya, S., Guo, W.*.(2018) Characterization of peach tree crown by using high-resolution images from an unmanned aerial vehicle. Horticulture Research. 5,1.
DOI:10.1038/s41438-018-0097-z

Guo, W.*, Zheng, B., Potgieter, A., Diot, J., Watanabe, K., Noshita, K., Jordan, D. Wang, X., Waston, J., Ninomiya, S., Chapman, S.C.(2018). Aerial imagery analysis-quantifying appearance and number of sorghum heads for applications in breeding and agronomy. Frontiers in Plant Science.9,1544.
DOI:10.3389/fpls.2018.01544

Fukano, Y., Guo, W., Noshita, K., Hashida, S., Kamikawa, S.(2018). Genotype-aggregated planting improves yield in Jerusalem artichoke (Helianthus tuberosus) due to self/non-self discrimination. Evolutionary Applications.

Fan X, Kawamura K, Guo W, et al (2017) A simple visible and near-infrared (V-NIR) camera system for monitoring the leaf area index and growth stage of Italian ryegrass. Comput Electron Agric. doi: 10.1016/j.compag.2017.11.025

Wei Guo , Bangyou Zheng, Tao Duan, Tokihiro Fukatsu, Scott Chapman, Seishi Ninomiya, EasyPCC: Benchmark Datasets and Tools for High-Throughput Measurement of the Plant Canopy Coverage Ratio under Field Conditions, Sensors 2017, 17, 798; doi:10.3390/s17040798

Yamamoto, K., T. Togami, N. Yamaguchi and S. Ninomiya (2017) Machine Learning-Based Calibration of Low-Cost Air Temperature Sensors Using Environmental Data. Sensors. 17:1290; doi:10.3390/s17061290

Duan, T., B Zheng, W Guo, S Ninomiya, Y Guo, SC Chapman, Comparison of ground cover estimates from experiment plots in cotton, sorghum and sugarcane based on images and ortho-mosaics captured by UAV, Functional Plant Biology 44 (1), 2017.

K. Watanabe，W. Guo， K. Arai， H. Takanashi， H. Kajiya-Kanegae， M. Kobayashi， K. Yano， T. Tsuyoshi， T. Fujiwara， N. Tsutsumi， H. Iwata. (2017) High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling. Frontiers in Plant Science，vol. 8，no.March，p.421，2017.

Elisa AA, Ninomiya S, Shamshuddin J, and Roslan I., Alleviating aluminum toxicity in an acid sulfate soil from Peninsular Malaysia by calcium silicate application. Solid Earth, 7, 2016, 367-374.

T. Duan, B. Zheng, W. Guo, S. Ninomiya, Y. Guo, S. C. Chapman. (2016) Comparison of ground cover estimates from experiment plots in cotton, sorghum and sugarcane based on images and ortho-mosaics captured by UAV, Functional Plant Biology, 44(1) 169-183, 2016.

K.Yamamoto, W. Guo, S. Ninomiya. (2016). Node Detection and Internode Length Estimation of Tomato Seedlings Based on Image Analysis and Machine Learning..Sensors. 2016; 16(7):1044 .

Guo W., Tokihiro Fukatsu,Seishi Ninomiya(2015). Automated characterization of flowering dynamics in rice using field-acquired time-series RGB images.Plant Methods 2015, 11:7 .

K.Yamamoto, S. Ninomiya,Y. Kimura, A. Hashimoto, Y. Yoshioka, T. Kameoka(2015). Strawberry cultivar identification and quality evaluation on the basis of multiple fruit appearance features.Computers and Electronics in Agriculture, 110,2015, 233-240.

J. Adinarayana, D. sudharsan, S. Ninomiya, M. Hirafuji and T. Kiura(2014). GeoSense: Decision support system for precsion faming in India. Wulfenia Journal, 22(2), 2015, 22–47.

A.K. Tripathy, J. Adinarayana, K.Vijayalakshmi, S.N. Merchant, U.B. Desai, S. Ninomiya, M. Hirafuji, T.Kiura(2014). Knowledge discovery and Leaf Spot dynamics of groundnut crop through wireless sensor network and data mining techniques. Computers and Electronics in Agriculture, 107, 2014, 104-114.

Kyosuke Yamamoto, Wei Guo, Yosuke Yoshioka, Seishi Ninomiya (2014). On plant detection of intact tomato fruits using image analysis and machine learning methods. Sensors, 14 (7), 2014, 12191-12206.

D. Sudharsan, J. Adinarayana, D. Raji Rddy, G. Sreeivas, S. Ninomiya, M. Hirafuji, T, Kiura, and K. Tanaka (2013). Evaluation of weather-based rice yield models in India. International Journal of Biometeorology, 57 (1), 2013, 107-123.

A K. Tripathy, J. Adinarayana, D. Sudharsan, S. N. Merchant, U. B. Desai, K. Vijayalakshmi, D. Raji Reddy, G. Sreenivas, S. Ninomiya, M Hirafuji, T. Kiura, K. Tanaka (2013). Data mining techniques for agriculture pest/disease prediction. Journal of Computer Information Systems and Industrial Management Applications, 5, 2013, 427-436.

平藤 雅之, 世一 秀雄, 三木 悠吾, 木浦 卓治, 深津 時広, 田中 慶, 松本 恵子, 星 典宏, 根角 博久, 澁谷 幸憲, 伊藤 淳士, 二宮 正士, Adinarayana J., Sudharsan D., 斉藤 保典, 小林 一樹, 鈴木 剛伸（2013）オープン・フィールドサーバ及びセンサクラウド・システムの開発，農業情報研究, 22, 2013, 60-70.

Wei Guo, Uday K. Rage, Seishi Ninomiya(2013),Illumination invariant segmentation of vegetation for time series wheat images based on decision tree model.Computers and Electronics in Agriculture, Computers and Electronics in Agriculture, 96, August 2013, 58-66.

Sudharsan, D., Adinarayana, J., Tripathy, a. K., Ninomiya, S., Hirafuji, M., Kiura, T., Desai, U.B., Merchant, S.N., Reddy, D.R., Sreenivas, G.(2012), GeoSense: A multimode information and communication system. ISRN Sensor Networks, 2012, Article ID 215103, 13 pages.

寺元郁博・二宮正士(2012). Web Map Serviceによる地図画像配信サービスの開発， 農業情報研究21(4), 2012,1-12.

Takashi Togami, Seishi Ninomiya, Kyosuke Yamamoto, Yumiko Mori, Toshiyuki Takasaki, Yasukazu Okano, Ryoichi Ikeda, Akane Takezaki, Takaharu Kameoka (2012). Field and weather monitoring with youths as sensors for agricultural decision support, Agricultural information Research 21(3),2012,65-75.

田中 慶, 木浦 卓治, 杉村 昌彦, 二宮 正士, 溝口 勝(2011). SIMRIWを利用した水稲栽培可能性予測支援ツール . 農業情報研究, 20(1), 2011, 1-12

高橋英博・吉川省子・鷹野洋・笹田康子・二宮正士(2011). 流域特性を考慮した岡山・香川流域から瀬戸内海への流入負荷量の推定, 陸水学雑誌 71，2010, 269-284.

Conference Paper

Wei Guo and Seishi Ninomiya. Field based phenotyping approaches by using time series images of paddy rice. Asia Pacific Advanced Network 38th meeting (APAN 38th), 11th-15th August, 2014, in Nantou, Taiwan..

Wei Guo and Seishi Ninomiya. Automatic determination of the daily flower appearance timing of paddy rice using field-acquired time-lapse images. 29-31 October, Phenoodays 2014, Palais des Congrès Beaune, France. .

Kyosuke Yamamoto, Wei Guo, Seishi Ninomiya. Tomato yield mapping in green house using color image analysis and machine learning method,18th World Congress of CIGR, 16th-19th, September, at Beijing, China,2014.

Wei Guo, Tokihiro Fukatsu, Seishi Ninomiya. Automatic detection of paddy rice flowering from time-series RGB images taken under outdoor environment,18th World Congress of CIGR(International Commission of Agricultural and Biosystems Engineering), 16th-19th, September, at Beijing, China,2014.

Wei Guo and Seishi Ninomiya. High throughput phenotyping tools for time series images in paddy fields. 9th Conference of the Asian Federation for Information Technology in Agriculture. 29th September-2nd October, in Perth, Australia,2014.

Seishi Ninomiya (2014) Agricultural knowledge transfer to illiterate farmers supported by children sensors: A case study in Vietnam, G-Space Workshop, 19 Feb, 2014, Komaba, Tokyo.

二宮正士（2013）情報科学が担う持続的な農業生産システム，日本農業工学会創立30周年記念シンポジウム，10月11日．

Seishi Ninomiya (2013) Service Innovations for Smart Agriculture, The 1st SRII Asia Summit 2013, Sept 17, 2013, Bangkok, Thailand.

西岡一洋（2013）樹液流センサの農業利用に向けた課題と展望について、計測と制御 52(8), 684-689, 2013-08.

二宮正士（2012）安全な食の確保，「未来を創る　半導体」IC Guide Book 2，JEITA, 72-75

Seishi Ninomiya (2012) Africa Network for Information Technology and Agriculture, IAALD African Chapter Conference, Johannesburg, South Africa, May 21-23, 2012.

Seishi Ninomiya, Yumi Mori, Toshiya Takasaki, Tranthin Hoa, Y. Okano, Takaharu Kameoka, S. Togami, A. Takezaki, R Ikeda, R. Ishida (2012) CHILDREN AS FIELD SENSORS - A TRIAL IN VIETNAM, Proc. CIGR-AgEng2012:1-5, Valencia, July 8-12, 2012 (CD).

Kyosuke Yamamoto, Takashi Togami, Atsushi Hashimoto, Yousuke Yoshioka, Seishi Ninomiya, Takaharu Kameoka (2012) A CHROMATIC IMAGE ANALYSIS FOR EVALUATING APPEARANCE OF AGRICULTURAL PRODUCTS USING COLOR DISTRIBUTION ENTROPY, Proc. CIGR-AgEng2012:1-6, Valencia, July 8-12, 2012 (CD).

S. Ninomiya, M. Mizoguchi, T. Hoa, Y. Mori, T. Takasaki, Y. Okano, K. Kameoka, S. Togami, H. Yamamoto, A. Takezaki, R. Ikeda, R. Ishida (2012) Children as Field Sensors to Support Site-specific Decisions in Rural Asia under Climatic Change, Proc. MARCO Symposium 2012, 61-63.

Kyosuke Yamamoto,Seishi Ninomiya,Yosuke Yoshioka,Takashi Togami,Atsushi Hashimoto,Takaharu Kameoka, Quality Evaluation and Cultivar Identification of Strawberry Using Image Analysis. AFITA/WCCA 2012, TaiWan, sept.2012.

Wei Guo,R. Uday Kiran,Seishi Ninomiya,Towards Effective Extraction of Green Fractional Vegetative Cover from Plant Images Taken under Natural Light. AFITA/WCCA 2012, TaiWan, sept.2012.

Yumi Mori,Toshiya Takasaki,Yasukazu Okano,Tran Ngan Thi Ngan Hoa,Takaharu Kameoka,Takashi Togami, Kyoshuke Yamamoto,Akane Takezaki,Ryoich Ikeda,Toru Ishida,Donghui Lin,Seishi Ninomiya, Youth Mediated Communication (YMC)- Agricultural Technology Transfer to Illiterate Farmers through Their Children. AFITA/WCCA 2012, TaiWan, sept.2012.

Hirafuji, M., H.Yoichi, T. Kiura, K., Matsumoto, H.Nesumi, N. Hoshi, S. Ninomiya, J. Adinarayana, D. Sudharsan, Y. Saito, K.Kobayashi, T. Suzuki, Ambient Sensor Cloud as A Solution of Practical Sensor Network in Agriculture,, APAN 31 meeting Workshop: Propagation of practical/advanced sensor network technologies, Hong Kong, 2011年2月24日

Masayuki Hirafuji, Hideo Yoichi, Takuji Kiura, Keiko Matsumoto, Tokihiro Fukatsu, Kei Tanaka, Yukinori Shibuya, Atsushi Itoh, Hirohisa Nesumi, Norihiro Hoshi, Seishi Ninomiya, J. Adinarayana, D. Sudharsan, Yasunori Saito, Kazuki Kobayashi, Takanobu Suzuki. 2011. Creating High-performance/Low-cost Ambient Sensor Cloud System Using OpenFS (Open Field Server) for High-throughput Phenotyping. SICE Annual Conference2011 Abstract CD:2090-2092

二宮正士　2011．情報技術を農業現場へ―農業情報学会．研究ジャーナル. 34(7):51

二宮正士, 農業グリッドが目指すもの, システム/制御/情報54(4)，155-161, 2010

二宮正士．2010．欧州の適正農業規範に学ぶ，バイオエタノール通信 2010年no.5，65-69

Hirafuji, Masayuki, Tokihiro Fukatsu, Takuji Kiura, Haoming Hu, Hideo Yoichi, Kei Tanaka, Yugo Miki, Seishi Ninomiya, Sensor Network Architecture Based on Web and Agent for Long-term Sustainable Observation in Open Fields, Advances in Practical Multi-Agent Systems, SCI325, Springrt-Verlag, Berlin Heidelberg, 425-433, 2010