GinJinn: An object-detection pipeline for automated feature extraction from herbarium specimens.

Tankred OttChristoph PalmRobert VogtChristoph Oberprieler

Published in: Applications in plant sciences (2020)

We establish GinJinn as a deep-learning object-detection tool for the automatic recognition and extraction of individual leaves or other structures from herbarium specimens. Our pipeline offers greater flexibility and a lower entrance barrier than previous image-processing approaches based on hand-crafted features.

Keyphrases

deep learning
artificial intelligence
machine learning
convolutional neural network
loop mediated isothermal amplification
working memory
real time pcr
label free
high resolution
high throughput
sensitive detection
quantum dots