, The GeoLifeCLEF 2020 Dataset". In: arXiv preprint, 2020.
URL : https://hal.archives-ouvertes.fr/hal-02989062
Overview of LifeCLEF location-based species prediction task 2020 (GeoLifeCLEF), CLEF task overview 2020, CLEF: Conference and Labs of the Evaluation Forum, 2020. ,
URL : https://hal.archives-ouvertes.fr/hal-02989077
Overview of LifeCLEF 2020: A System-Oriented Evaluation of Automated Species Identification and Species Distribution Prediction, Lecture Notes in Computer Science, pp.342-363, 2020. ,
URL : https://hal.archives-ouvertes.fr/hal-02945382
Overview of GeoLifeCLEF 2019: plant species prediction using environment and animal occurrences, CLEF task overview 2019, CLEF: Conference and Labs of the Evaluation Forum, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02190170
Location-Based Plant Species Prediction Using A CNN Model Trained On Several Kingdoms-Best Method Of GeoLifeCLEF 2019 Challenge, CLEF working notes 2019, CLEF: Conference and Labs of the Evaluation Forum, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02392637
Overview of GeoLifeCLEF 2018: location-based species recommendation, CLEF task overview 2018, CLEF: Conference and Labs of the Evaluation Forum, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01913238
A Deep Learning Approach to Species Distribution Modelling, Multimedia Tools and Applications for Environmental & Biodiversity Informatics, pp.169-199, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01834227
Pl@ntnet app in the era of deep learning, ICLR 2017 Workshop Track-5th International Conference on Learning Representations, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01629195
Rethinking the Inception Architecture for Computer Vision, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2818-2826, 2016. ,
Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00650905