# Pl@ntNet Pl@ntNet identifica plantas por fotos e apoia a pesquisa sobre biodiversidade na web, Android e iOS. - Findings24: - Site: - Preços: Freemium - Categorias: Reconhecimento de Imagem IA ## O que é Pl@ntNet? Pl@ntNet is a citizen-science platform for identifying and inventorying plant species from photos. It combines a plant-recognition application with a community review process and a broader biodiversity data project. The product is available on the web and on smartphones for Android and iOS. Users can submit plant photos, receive identification help, and, if they create an account, contribute observations that may be reviewed by the community and used to improve the AI model and public biodiversity datasets. ## O que Pl@ntNet pode fazer? ### Photo-based plant identification Identify plants from photos in the web app or mobile app by using image recognition to compare submitted images with the platform’s species database. ### Web and mobile access Use the service on both smartphone and browser, with explicit support for Android, iOS, and the web. ### Community observation sharing Create an account to share observations that can be reviewed by the community and contribute to the platform’s learning loop. ### Community revision Confirm a suggested species or propose a different determination when you have botanical knowledge, adding human review to the workflow. ### Research-oriented data contribution Contribute geolocated observations that may later support mapping and biodiversity research, with GPS data highlighted as important. ### Periodic model retraining Benefit from a model that is retrained regularly, described as roughly monthly, to incorporate new observations and revisions. ## Casos de uso ### Identify a plant from a photo Take a picture of an unknown plant and use the web or mobile app to get an identification suggestion based on image recognition. ### Contribute to citizen-science observation collection Share your own observations from a created account so they can be reviewed by other users and potentially contribute to the AI model. ### Review and revise observations Confirm or correct a proposed species identification if you have botanical expertise, helping improve the quality of shared observations. ### Support biodiversity research Record geolocated plant sightings for biodiversity mapping and research projects that rely on public observation data. ### Learn how to photograph plants effectively Use the help pages on iOS or Android to learn how to capture better plant photos before submitting observations. ## Perguntas frequentes ### On which platforms can I use Pl@ntNet? Pl@ntNet is available on the web and on smartphones, with versions for Android and iOS. The site also points users to specific guidance for iOS and Android in its usage help pages. ### What kind of photos does Pl@ntNet need? Pl@ntNet uses image recognition, so it works best with clear photos. The help page advises taking good-quality images and sharing several photos of the plant organs when possible. ### How does community review work? Users can share observations from a created account. Those observations may be reviewed by the community and, when they reach sufficient confidence, added to the public database and used to train the AI. ### Is Pl@ntNet free to use? The site presents Pl@ntNet as a free participatory science platform, supported by donations, with no advertising and no resale of data. ### Are all observations published and used for research? Not every observation is shared. The site notes that only observations with enough confidence and acceptable image quality are added to the public database, and GPS location is important for mapping species. ## Informações rápidas - **Category**: Citizen science / plant identification - **Platforms**: Web, Android, iOS - **Primary users**: People identifying plants and contributors to biodiversity observation - **Source domain**: plantnet.org - **Pricing**: Free to use; supported by donations - **Data workflow**: Photo upload, community review, AI retraining, public biodiversity datasets