Image-based plant identification
102 days left
Note: Do not forget to read the Rules section on this page
Automated identification of plants has improved considerably in the last few years. In the scope of LifeCLEF 2017 and 2018 in particular, we measured impressive identification performance over 10K species. However, these 10K species, mostly living in Europe and North America, only represent the tip of the iceberg. The vast majority of the species in the world (~369K species) actually lives in data deficient countries and the performance of state-of-the-art machine learning algorithms on these species is unknown and presumably much lower because of the weak amount of training data. Thus, the main novelty of the 2019 edition of PlantCLEF will be to extend the challenge to the flora of such data deficient countries.
The goal of the task will be to return the most likely species for each observation of the test set (an observation being a set of images of the same individual plants+metadata). The test set will be composed of two subsets, one covering data-abundant species and one covering data-deficient species.
In addition to the 10K species dataset provided last year (built from data abundant regions), we will provide a new 10K species dataset built from four distinct data-deficient regions in the world (South Africa, French Guyana, Laos and tropical belt). The average number of images per species in that new dataset will be much lower (about 10 vs. 100 for data-abundant regions one). Many species will contain only a few images and some of them might even contain only 1 image.
The training data will be delivered around the 1st of February 2019. The test set ti be predicted will be delivered around the 1st of March 2019.
More practically, the run file to be submitted has to contain as much lines as the number of predictions, each prediction being composed of an ObservationId (the identifier of a specimen that can be itself composed of several images), a ClassId, a Probability and a Rank (used in case of equal probabilities). Each line should have the following format: <ObservationId;ClassId;Probability;Rank>
Here is a short fake run example respecting this format for only 3 observations: fake_run
As soon as the submission is open, you will find a “Create Submission” button on this page (just next to the tabs)
The used metric will be the Mean Reciprocal Rank ( MRR ). The MRR is a statistic measure for evaluating any process that produces a list of possible responses to a sample of queries ordered by probability of correctness. The reciprocal rank of a query response is the multiplicative inverse of the rank of the first correct answer. The MRR is the average of the reciprocal ranks for the whole test set.
LifeCLEF lab is part of the Conference and Labs of the Evaluation Forum: CLEF 2019. CLEF 2019 consists of independent peer-reviewed workshops on a broad range of challenges in the fields of multilingual and multimodal information access evaluation, and a set of benchmarking activities carried in various labs designed to test different aspects of mono and cross-language Information retrieval systems. More details about the conference can be found here .
Submitting a working note with the full description of the methods used in each run is mandatory. Any run that could not be reproduced thanks to its description in the working notes might be removed from the official publication of the results. Working notes are published within CEUR-WS proceedings, resulting in an assignment of an individual DOI (URN) and an indexing by many bibliography systems including DBLP. According to the CEUR-WS policies, a light review of the working notes will be conducted by LifeCLEF organizing committee to ensure quality. As an illustration, LifeCLEF 2018 working notes (task overviews and participant working notes) can be found within CLEF 2018 CEUR-WS proceedings.
Participants of this challenge will automatically be registered at CLEF 2019. In order to be compliant with the CLEF registration requirements, please edit your profile by providing the following additional information:
Regarding the username, please choose a name that represents your team.
This information will not be publicly visible and will be exclusively used to contact you and to send the registration data to CLEF, which is the main organizer of all CLEF labs
LifeCLEF 20189 is an evaluation campaign that is being organized as part of the CLEF initiative labs. The campaign offers several research tasks that welcome participation from teams around the world. The results of the campaign appear in the working notes proceedings, published by CEUR Workshop Proceedings (CEUR-WS.org). Selected contributions among the participants, will be invited for publication in the following year in the Springer Lecture Notes in Computer Science (LNCS) together with the annual lab overviews.
- Discussion Forum : https://www.crowdai.org/challenges/lifeclef-2019-plant/topics
We strongly encourage you to use the public channels mentioned above for communications between the participants and the organizers. In extreme cases, if there are any queries or comments that you would like to make using a private communication channel, then you can send us an email at lifeclef-org[AT]inria[DOT]fr
You can find additional information on the challenge here: https://www.imageclef.org/PlantCLEF2019