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Publications

Publications from Imageomics groups (Methods in Ecology and Evolution format)

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This repository has not been maintained and its content is thus very far from up to date. It was superseded by the Imageomics Group library on Zotero, which should be consulted instead.

  1. Leipzig, J., Bakis, Y., Wang, X., Elhamod, M., Diamond, K., Dahdul, W., Karpatne, A., Maga, M., Mabee, P., Bart, H. L., & Greenberg, J. (2021). Biodiversity Image Quality Metadata Augments Convolutional Neural Network Classification of Fish Species. In E. Garoufallou & M.-A. Ovalle-Perandones (Eds.), Metadata and Semantic Research (pp. 3–12). Springer International Publishing. https://doi.org/10.1007/978-3-030-71903-6_1
  2. Diamond, K. M., Rolfe, S. M., Kwon, R. Y., & Maga, A. M. (2022). Computational anatomy and geometric shape analysis enables analysis of complex craniofacial phenotypes in zebrafish. Biology Open, 11(2), bio058948. https://doi.org/10.1242/bio.058948
  3. Elhamod, M., Diamond, K. M., Maga, A. M., Bakis, Y., Bart Jr., H. L., Mabee, P., Dahdul, W., Leipzig, J., Greenberg, J., Avants, B., & Karpatne, A. (2022). Hierarchy-guided neural network for species classification. Methods in Ecology and Evolution, 13(3), 642–652. https://doi.org/10.1111/2041-210X.13768
  4. Song, C. H., Kil, J., Pan, T.-Y., Sadler, B. M., Chao, W.-L., & Su, Y. (2022). One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones. arXiv [cs.AI]. Retrieved from http://arxiv.org/abs/2202.07028
  5. Tuia, D., Kellenberger, B., Beery, S., Costelloe, B. R., Zuffi, S., Risse, B., … Berger-Wolf, T. (2022). Perspectives in machine learning for wildlife conservation. Nature Communications, 13(1), 1–15. http://dx.doi.org/10.1038/s41467-022-27980-y
  6. Rolfe, S. M., & Maga, A. M. (2022). Deep Learning Enabled Multi-Organ Segmentation of Mouse Embryos (p. 2022.08.26.505447). bioRxiv. https://doi.org/10.1101/2022.08.26.505447

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