Grants and residencies Research MA Sipilä Ilkka 15000 € Grant year 2021 Share: Back to Grants listing Applying supervised deep transfer learning convolutional neural networks to the classification of palaeoenvironmental remains Tieteellinen tutkimus / siihen pohjautuva työ | Yksivuotinen This doctoral thesis is an interdisciplinary investigation of the subjectivity inherent in the analysts’ classifications of palaeoenvironmental remains, namely pollen grains and faunal osseous remains. The significant research contributions span from improvements in the post-hoc interpretation of convolutional neural networks, state-of-the-art classification models in pollen classification, and the first application of convolutional neural networks in the classification of bones to species from images. Back to Grants listing