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2022
Journal article
Harnessing Large-Scale Herbarium Image Datasets Through Representation Learning.
The mobilization of large-scale datasets of specimen images and metadata through herbarium digitization provide a rich environment for the application and development of machine learning techniques. However, limited access to computational resources and uneven progress in digitization, especially for small herbaria, still present barriers to the wide adoption of these...Walker, Barnaby E. ; Tucker, Allan ; Nicolson, Nicky
Machine learning, Natural history collections, Digitized herbarium specimens, Deep learning, and Computer vision
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2019
Doctoral thesis
Automating the construction of higher order data representations from heterogeneous biodiversity datasets
Datasets created from large-scale specimen digitisation drive biodiversity research, but these are often heterogeneous: incomplete and fragmented. As aggregated data volumes increase, there have been calls to develop a “biodiversity knowledge graph” to better interconnect the data and support meta-analysis, particularly relating to the process of species description. This work...Nicolson, Nicky
Clustering, Specimen digitisation, Biodiversity informatics, Machine learning, and Record linkage