ELPephants: A Fine-Grained Dataset for Elephant Re-IdentificationMatthias Körschens, Joachim Denzler|Unknown|2019Cited by 42
Towards Automatic Identification of Elephants in the WildMatthias Körschens, Joachim Denzler, Björn Barz|arXiv (Cornell University)|2018Cited by 31
Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research—Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apesPaul Bodesheim, Joachim Denzler, Matthias Körschens et al.|Mammalian Biology|2022Cited by 21
Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised LocalizationMatthias Körschens, Joachim Denzler, Paul Bodesheim|Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications|2022Cited by 9
Determining the community composition of herbaceous species from images using convolutional neural networksMatthias Körschens, Christine Römermann, Joachim Denzler et al.|Ecological Informatics|2024Cited by 7