Παρακολούθηση
Vamsi Krishna Kommineni
Vamsi Krishna Kommineni
PhD candidate, Friedrich-Schiller-Universität Jena
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα uni-jena.de - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries
VK Kommineni, S Tautenhahn, P Baddam, J Gaikwad, B Wieczorek, ...
Biodiversity Data Journal 9 (e69806), 2021
82021
Understanding intraspecific trait variability using digital herbarium specimen images
VK Kommineni, J Kattge, J Gaikwad, P Baddam, S Tautenhahn
Biodiversity Information Science and Standards 4, e59061, 2020
32020
Envisaging a global infrastructure to exploit the potential of digitised collections
Q Groom, M Dillen, W Addink, AHH Ariño, C Bölling, P Bonnet, L Cecchi, ...
Biodiversity Data Journal 11, 2023
22023
How Reproducible are the Results Gained with the Help of Deep Learning Methods in Biodiversity Research?
W Ahmed, VK Kommineni, B Koenig-ries, S Samuel
Biodiversity Information Science and Standards 7, 2023
22023
From human experts to machines: An LLM supported approach to ontology and knowledge graph construction
VK Kommineni, B König-Ries, S Samuel
arXiv preprint arXiv:2403.08345, 2024
12024
From human experts to machines: An LLM supported approach to ontology and knowledge graph construction
KK Vamsi, VK Kommineni, S Samuel
2024
The Role of the CLIP Model in Analysing Herbarium Specimen Images
VK Kommineni, J Kattge, J Gaikwad, S Tautenhahn, B Koenig-ries
Biodiversity Information Science and Standards 7, 2023
2023
Evaluating global patterns of leaf area using Machine Learning approache
VK Kommineni
Ernst Abbe University of Applied Sciences Jena Jena, 2020
2020
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