Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Vamsi Krishna Kommineni"'
Autor:
Quentin Groom, Mathias Dillen, Wouter Addink, Arturo H. Ariño, Christian Bölling, Pierre Bonnet, Lorenzo Cecchi, Elizabeth R. Ellwood, Rui Figueira, Pierre-Yves Gagnier, Olwen Grace, Anton Güntsch, Helen Hardy, Pieter Huybrechts, Roger Hyam, Alexis Joly, Vamsi Krishna Kommineni, Isabel Larridon, Laurence Livermore, Ricardo Jorge Lopes, Sofie Meeus, Jeremy Miller, Kenzo Milleville, Renato Panda, Marc Pignal, Jorrit Poelen, Blagoj Ristevski, Tim Robertson, Ana Rufino, Joaquim Santos, Maarten Schermer, Ben Scott, Katja Seltmann, Heliana Teixeira, Maarten Trekels, Jitendra Gaikwad
Publikováno v:
Biodiversity Data Journal, Vol 11, Iss , Pp 1-29 (2023)
Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine lear
Externí odkaz:
https://doaj.org/article/4e28fb68392945698dd41af6bd879cec
Autor:
Vamsi Krishna Kommineni, Susanne Tautenhahn, Pramod Baddam, Jitendra Gaikwad, Barbara Wieczorek, Abdelaziz Triki, Jens Kattge
Publikováno v:
Biodiversity Data Journal, Vol 9, Iss , Pp 1-41 (2021)
Morphological leaf traits are frequently used to quantify, understand and predict plant and vegetation functional diversity and ecology, including environmental and climate change responses. Although morphological leaf traits are easy to measure, the
Externí odkaz:
https://doaj.org/article/22c6987e92334127a166e9a834adf6dd
Autor:
Quentin Groom, Mathias Dillen, Wouter Addink, Arturo H. Ariño, Christian Bölling, Pierre Bonnet, Lorenzo Cecchi, Elizabeth R. Ellwood, Rui Figueira, Pierre-Yves Gagnier, Olwen Grace, Anton Güntsch, Helen Hardy, Pieter Huybrechts, Roger Hyam, Alexis Joly, Isabel Larridon, Vamsi Krishna Kommineni, Laurence Livermore, Ricardo Jorge Lopes, Jeremy Miller, Sofie Meeus, Kenzo Milleville, Marc Pignal, Renato Panda, Jorrit H. Poelen, Blagoj Ristevski, Tim Robertson, Cristina Rufino, Joaquim Santos, Maarten Schermer, Katja Seltmann, Ben Scott, Heliana Teixeira, Maarten Trekels, Jitendra Gaikwad
Tens of millions of images from biological collections have become available online in the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e837d0f8f0783700dde14cd4bef2779
https://inria.hal.science/hal-03871553
https://inria.hal.science/hal-03871553
Publikováno v:
Biodiversity Information Science and Standards 4: e59061
Plant traits are vital to quantify, understand and predict plant and vegetation ecology, including responses to environmental and climate change. Leaf traits are among the best sampled, with more than 200,000 records for individual traits. Neverthele
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b858b9c6ad73837542b1fecffdcaf914
https://zenodo.org/record/4074685
https://zenodo.org/record/4074685