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A machine learning approach for cross-domain plant identification using herbarium specimens

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Comparing HFTL and OSM Networks in the context of Cross-Domain Plant Identification

This repository contains the implementation method of our Herbarium-Field Triplet Loss Network (HFTL Network) and One-streamed Mixed Network (OSM Network) in the context of Cross-Domain Plant Identification. Our results show that the HFTL Network can generalize rare species as equally as species with many training data better than the OSM Network (conventional CNNs).

Figure A and B below show the Top-5 predictions of a plant sample with its predicted scores and activation maps from the HFTL and OSM Networks respectively. More samples of comparison can be found here.

HFTL Network OSM Network
Figure 1 Figure 2

Research article

A machine learning approach for cross-domain plant identification using herbarium specimens
https://doi.org/10.1007/s00521-022-07951-6

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Data

Scripts

Training scripts

Validation scripts

Visualizing activation map scripts

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Herbarium Network

Field Network (2017)

Field Network (2021)

HFTL Network

OSM Network

Herbarium Dictionary

Test Sets

Checkpoints / Trained models

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A machine learning approach for cross-domain plant identification using herbarium specimens

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