Pl@ntNet - Universal application for identifying plants from photos.
Image-based plant identification
Pl@ntNet is a participatory science project accessible in the form of a plant identification application based on your photos and an A.I. trained to recognize them.
Over 73,000 plant species are identified, accompanied by over 1 billion images. Each plant can be identified at different stages of its development, by its flowers, leaves, fruit, bark or other plant-specific characteristics.
Data modeled in graphs (which can be multi-dimensional) allow the detection of relationships that are practically invisible in other forms and, above all, with much less computational and energy resources.
hwloc is an open-source software package now used worldwide and made available by the Inria Center at the University of Bordeaux since 2009. Without hwloc's mapping capabilities, trying to find the best way to organize your calculations would be a trial-and-error process.
How can we ensure that administrative algorithms apply the law as interpreted by administrative legal departments, without distortion or approximation?
It's hard for applications' graphical interfaces to reveal their full functionality, even less so on phones where menus are reduced to their simplest expression. INRIA is working to improve the situation.