Presentations at CCE’23

Masatoshi Funabashi , Sony CSL senior reseacher, presented two research papers at the Complex Computational Ecosystems 2023 in Baku, Azerbaijan, and one of them received the Best Non-Student Presentation Award.

■ [Best Non-Student Presentation Award ] “Vegee Brain Automata: Ultradiscretization of essential chaos transversal in neural and ecosystem dynamics” (Masatoshi Funabashi)

Get the final version manuscript here.

■“Modeling ecosystem management based on the integration of image analysis and human subjective evaluation – Case studies with synecological farming” (Shuntaro Aotake, Atsuo Takanishi, Masatoshi Funabashi

Get the final version manuscript here.

Both papers have been published in Springer Lecture Notes in Computation Science.

日本ロボット学会誌に論文発表

日本ロボット学会誌40 巻 (2022) 9 号に、以下の論文が公開されました。

協生農法環境における農作業支援ロボットの開発—第1報:圃場移動の開発および剪定・収穫動作の実現—田中 大雅, 政谷 巧樹, 寺江 航汰, 水上 英紀, 村上 将嗣, 吉田 駿也, 青竹 峻太郎, 舩橋 真俊, 大谷 拓也, 高西 淳夫

(English Title: Development of the Agricultural Robot in SynecocultureTM Environment —1st Report, Development of Moving Mechanism on the Farm and Realization of Weeding and Harvesting—)

Opinion Article in BiodiverCities by 2030

An opinion article on Synecoculture and urban augmented ecosystems was published in the book “BiodiverCities by 2030: Transforming Cities with Biodiversity”:

Funabashi, M. Living in a Hotspot of City and Biodiversity. The Case of Synecoculture. P. 252-253. In: Mejía, M.A., Amaya-Espinel, J.D. (eds.). BiodiverCities by 2030: Transforming Cities with Biodiversity. Bogotá. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt. 2022. 288 pages.

第49回画像電子学会年次大会にて発表

Sony CSLより青竹峻太郎・舩橋真俊が参画した、協生農法に関する早稲田大学との共同研究について、以下の通り学会発表を行いました。

2021 年度 第 49 回画像電子学会年次大会
Media Computing Conference 2021
https://www.iieej.org/annualconf/2021nenji-top/

6月26日(土)

●16:00-16:45 学生セッション(S7) 3件 「動物」 (15分/件) 座長:森谷友昭(東京電機大学)

【S7-3】協生農法環境におけるRGB画像からの圃場の優勢植生の深層学習を用いる検出方法に関する研究
 〇征矢寛汰(早稲田大学) , 青竹峻太郎(早稲田大学/ソニーコンヒ゜ュータサイエンス研究所), 小方博之(早稲田大学/成蹊大学), 大谷 淳, 大谷拓也, 高西淳夫(早稲田大学), 舩橋真俊(ソニーコンヒ゜ュータサイエンス研究所)

●16:55-17:40 学生セッション(S8) 3件 「動物」 (15分/件) 座長:小林直樹(埼玉医科大学)

【S8-2】協生農法環境におけるRGB画像に対するSemantic Segmentationを用いた圃場の被覆状態の認識方法に関する研究
 〇吉崎玲奈(早稲田大学) , 青竹峻太郎(早稲田大学/ソニーコンヒ゜ュータサイエンス研究所), 小方博之(早稲田大学/成蹊大学), 大谷 淳, 大谷拓也, 高西淳夫(早稲田大学), 舩橋真俊(ソニーコンヒ゜ュータサイエンス研究所)

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English :

The Institute of Image Electronics Engineers of Japan(IIEEJ)
Media Computing Conference 2021

6/26

Student Session(S7) “Animal Session”

●【S7-3】 Study of a method for detecting dominant vegetation in a field from RGB images using deep learning in Synecoculture environment

        〇Kanta SOYA*1, Shuntaro AOTAKE*2/*3, Hiroyuki Ogata*4/*5, Jun OHYA*6, Takuya OHTANI*7, Atsuo TAKANISHI*6, Masatoshi FUNABASHI*3

        *1 Dept. of Modern Mechanical Engineering, WASEDA University, *2 Dept. of Advanced Science and Engineering, WASEDA University, *3 Sony Computer Science Laboratories, Inc, *4 Waseda University, Future Robotics Organization, *5 Dept. of System Design, SEIKEI University, *6 Dept. of Modern Mechanical Engineering, WASEDA University, *7 Waseda Research Institute for Science and Engineering

Student Session(S8) ”Animal Session”

●【S8-2】 Study of a Method for Recognizing Field Covering Situation by Applying Semantic Segmentation to RGB Images in Synecoculture Environment

        〇Reina YOSHIZAKI1,Shuntaro AOTAKE2,3,Hiroyuki OGATA4,5,Jun OHYA1,Takuya OHTANI6,Atsuo TAKANISHI1,Masatoshi FUNABASHI3

        1 Graduate School of Creative Science and Engineering, Waseda University,2 Graduate School of Advanced Science and Engineering, Waseda University,3 Sony Computer Science Laboratories, Inc.,4 Faculty of Science and Technology, Seikei University,5 Waseda University, Future Robotics Organization,6 Waseda Research Institute for Science and Engineering

Article “Secondary Metabolite Differences between Naturally Grown and Conventional Coarse Green Tea” published from the Agriculture journal

The following article was published from the MDPI journal Agriculture, in the Special Issue Secondary Metabolites in Plant-Microbe Interactions:

Ohta, K.; Kawaoka, T.; Funabashi, M. Secondary Metabolite Differences between Naturally Grown and Conventional Coarse Green Tea. Agriculture202010, 632.

Metabolic map projection of Synecoculture-distinctive compounds (yellow) and conventional monoculture-distinctive compounds (blue) of green coarse tea (see Supplementary Material S17 of the article)