Multi-class classification problem is among the most popular and well-studied statistical
frameworks. Modern multi-class datasets can be extremely ambiguous and single-output …

We use deep convolutional neural networks to identify the plant species captured in a
photograph and evaluate different factors affecting the performance of these networks. Three …

Blind people often need to identify objects around them, from packages of food to items of
clothing. Automatic object recognition continues to provide limited assistance in such tasks …

Classification of plants based on a multi-organ approach is very challenging. Although
additional data provide more information that might help to disambiguate between species …

The LifeCLEFs plant identication task provides a testbed for a system-oriented evaluation of
plant identication about 500 species trees and herbaceous plants. Seven types of image …

Using multimedia identification tools is considered as one of the most promising solutions to
help bridging the taxonomic gap and build accurate knowledge of the identity, the …

Tree species identification using bark images is a challenging problem that could prove
useful for many forestry related tasks. However, while the recent progress in deep learning …

Background Deep learning algorithms for automated plant identification need large
quantities of precisely labelled images in order to produce reliable classification results …

Background Fine-grained recognition of plants from images is a challenging computer vision
task, due to the diverse appearance and complex structure of plants, high intra-class …

Background Automated species identification is a long term research subject. Contrary to
flowers and fruits, leaves are available throughout most of the year. Offering margin and …