Skip to content

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

License

Notifications You must be signed in to change notification settings

NeuonAI/hftl_osm_visuals

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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

Requirements


Data

Scripts

Training scripts

Validation scripts

Visualizing activation map scripts

Lists

Herbarium Network

Field Network (2017)

Field Network (2021)

HFTL Network

OSM Network

Herbarium Dictionary

Test Sets

Checkpoints / Trained models

About

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

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages