Image-based Plant Species Identification with Deep Convolutional Neural Networks

  title={Image-based Plant Species Identification with Deep Convolutional Neural Networks},
  author={Mario Lasseck},
This paper presents deep learning techniques for image-based plant identification at very large scale. State-of-the-art Deep Convolutional Neural Networks (DCNNs) are fine-tuned to classify 10,000 species. To improve identification performance several models trained on different datasets with multiple image dimensions and aspect ratios are ensembled. Various data augmentation techniques have been applied to prevent overfitting and to further improve model accuracy and generalization. The… CONTINUE READING
Highly Cited
This paper has 21 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 11 extracted citations


Publications referenced by this paper.
Showing 1-10 of 23 references

ImageNet Large Scale Visual Recognition Challenge

International Journal of Computer Vision • 2015
View 5 Excerpts
Highly Influenced

Lab Overview: multimedia species identification challenges

A Joly, H Goëau, +7 authors H Müller
LifeCLEF • 2017

Deep Residual Learning for Image Recognition

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2016

Similar Papers

Loading similar papers…