Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Masahiro Ryo"'
Publikováno v:
ISPRS Open Journal of Photogrammetry and Remote Sensing, Vol 12, Iss , Pp 100064- (2024)
Predicting crop yield using deep learning (DL) and remote sensing is a promising technique in agriculture. In smallholder agriculture (
Externí odkaz:
https://doaj.org/article/180e4649d8e345f2880fc51fef475521
Autor:
Juan Camilo Rivera Palacio, Christian Bunn, Eric Rahn, Daisy Little-Savage, Paul Günter Schmidt, Masahiro Ryo
Publikováno v:
Plant Phenomics, Vol 6 (2024)
Deep learning and computer vision, using remote sensing and drones, are 2 promising nondestructive methods for plant monitoring and phenotyping. However, their applications are infeasible for many crop systems under tree canopies, such as coffee crop
Externí odkaz:
https://doaj.org/article/2ca9e6b18c5e4bed887c7061ccdf78cc
Autor:
Anastasiia Safonova, Gohar Ghazaryan, Stefan Stiller, Magdalena Main-Knorn, Claas Nendel, Masahiro Ryo
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 125, Iss , Pp 103569- (2023)
Researchers and engineers have increasingly used Deep Learning (DL) for a variety of Remote Sensing (RS) tasks. However, data from local observations or via ground truth is often quite limited for training DL models, especially when these models repr
Externí odkaz:
https://doaj.org/article/6994e712fa75445da5fab585d52262e1
Autor:
Masahiro Ryo, Josepha Schiller, Stefan Stiller, Juan Camilo Rivera Palacio, Konlavach Mengsuwan, Anastasiia Safonova, Yuqi Wei
Publikováno v:
Journal of Sustainable Agriculture and Environment, Vol 2, Iss 1, Pp 40-44 (2023)
Abstract Deep learning is an emerging data analytic tool that can improve predictability, efficiency and sustainability in agriculture. With a bibliometric analysis of 156 articles, we show how deep learning methods have been applied in the context o
Externí odkaz:
https://doaj.org/article/899cc1d3f65d4bfe85c5f2b9216ddd19
Autor:
Karin Pirhofer Walzl, Masahiro Ryo, Larissa Raatz, Jana S. Petermann, Arthur Gessler, Jasmin Joshi, Matthias C. Rillig
Publikováno v:
Journal of Sustainable Agriculture and Environment, Vol 1, Iss 4, Pp 262-274 (2022)
Abstract Introduction The proximity of semi‐natural habitats and agricultural fields in an agricultural landscape leads to unavoidable biological, chemical, and physical interactions. Fungi can negatively influence, but also support crop growth in
Externí odkaz:
https://doaj.org/article/640185e7a24c4801974d455aefbb63f0
Autor:
Gaowen Yang, Masahiro Ryo, Julien Roy, Daniel R. Lammel, Max-Bernhard Ballhausen, Xin Jing, Xuefeng Zhu, Matthias C. Rillig
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-8 (2022)
It is unclear whether the positive effects of biodiversity on ecosystem functioning are maintained under multifaceted anthropogenic disturbance. In this experiment, the authors show that multiple simultaneous stressors can negate the positive effect
Externí odkaz:
https://doaj.org/article/5379e1c5962f4cc1a3e83348cc786dc2
Autor:
Romy Breitenbach, Ruben Gerrits, Polina Dementyeva, Nicole Knabe, Julia Schumacher, Ines Feldmann, Jörg Radnik, Masahiro Ryo, Anna A. Gorbushina
Publikováno v:
npj Materials Degradation, Vol 6, Iss 1, Pp 1-11 (2022)
Abstract The roles extracellular polymeric substances (EPS) play in mineral attachment and weathering were studied using genetically modified biofilms of the rock-inhabiting fungus Knufia petricola strain A95. Mutants deficient in melanin and/or caro
Externí odkaz:
https://doaj.org/article/3b25e4ed98b04a0a8858fa9c88a4e5b0
Autor:
Masahiro Ryo
Publikováno v:
Artificial Intelligence in Agriculture, Vol 6, Iss , Pp 257-265 (2022)
Artificial intelligence and machine learning have been increasingly applied for prediction in agricultural science. However, many models are typically black boxes, meaning we cannot explain what the models learned from the data and the reasons behind
Externí odkaz:
https://doaj.org/article/d27391a00a4843cb8ab72a17df19e65e
Autor:
Matthias C Rillig, Milos Bielcik, V Bala Chaudhary, Leonie Grünfeld, Stefanie Maaß, India Mansour, Masahiro Ryo, Stavros D Veresoglou
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 11, p e1008313 (2020)
When running a lab we do not think about calamities, since they are rare events for which we cannot plan while we are busy with the day-to-day management and intellectual challenges of a research lab. No lab team can be prepared for something like a
Externí odkaz:
https://doaj.org/article/be9b7f2d0ce84a9fb27b88555d789d12
Publikováno v:
Frontiers in Microbiology, Vol 11 (2020)
As a consequence of ongoing climate change, the frequency of extreme heat events is expected to increase. Recurring heat pulses may disrupt functions supported by soil microorganisms, thus affecting the entire ecosystem. However, most perturbation ex
Externí odkaz:
https://doaj.org/article/d543a493a58c42729cfbfba5095616c4