Pl@ntNet app in the era of deep learning

Affouard Antoine, Goeau Hervé, Bonnet Pierre, Lombardo Jean-Christophe, Joly Alexis. 2017. Pl@ntNet app in the era of deep learning. . Toulon : s.n., 6 p. International Conference on Learning Representations. 5, Toulon, France, 24 April 2017/26 April 2017.

Paper without proceedings
Published version - Anglais
License CC0 1.0 Public Domain Dedication.

Télécharger (1MB) | Preview

Abstract : Pl@ntNet is a large-scale participatory platform and information system dedicated to the production of botanical data through image-based plant identification. In June 2015, Pl@ntNet mobile front-ends moved from classical hand-crafted visual features to deep-learning based image representations. This paper gives an overview of today's Pl@ntNet architecture and discusses how the introduction of convolutional neural networks did improve the whole workflow along the years. (Résumé d'auteur)

Classification Agris : F70 - Plant taxonomy and geography
C30 - Documentation and information
C20 - Extension

Auteurs et affiliations

  • Affouard Antoine, CIRAD-BIOS-UMR AMAP (FRA)
  • Goeau Hervé, CIRAD-BIOS-UMR AMAP (FRA)
  • Bonnet Pierre, CIRAD-BIOS-UMR AMAP (FRA) ORCID: 0000-0002-2828-4389
  • Lombardo Jean-Christophe, INRIA (FRA)
  • Joly Alexis, INRIA (FRA)

Source : Cirad-Agritrop (

View Item (staff only) View Item (staff only)

[ Page générée et mise en cache le 2020-11-23 ]