AIMC Topic: Fossils

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Artificial intelligence provides greater accuracy in the classification of modern and ancient bone surface modifications.

Scientific reports Nov 2, 2020
Bone surface modifications are foundational to the correct identification of hominin butchery traces in the archaeological record. Until present, no analytical technique existed that could provide objectivity, high accuracy, and an estimate of probab...
Animals Africa Europe Humans Artificial Intelligence Archaeology Fossils Hominidae Bone and Bones Tooth
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Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy.

Proceedings of the National Academy of Sciences of the United States of America Oct 23, 2020
Taxonomic resolution is a major challenge in palynology, largely limiting the ecological and evolutionary interpretations possible with deep-time fossil pollen data. We present an approach for fossil pollen analysis that uses optical superresolution ...
South America Pollen Phylogeography Africa, Western Fossils Phylogeny Neural Networks, Computer Africa Machine Learning Microscopy
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Neural networks differentiate between Middle and Later Stone Age lithic assemblages in eastern Africa.

PloS one Aug 26, 2020
The Middle to Later Stone Age transition marks a major change in how Late Pleistocene African populations produced and used stone tool kits, but is manifest in various ways, places and times across the continent. Alongside changing patterns of raw ma...
Humans Neural Networks, Computer Africa, Eastern Archaeology Fossils Animals Geologic Sediments
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Deep learning and taphonomy: high accuracy in the classification of cut marks made on fleshed and defleshed bones using convolutional neural networks.

Scientific reports Dec 12, 2019
Accurate identification of bone surface modifications (BSM) is crucial for the taphonomic understanding of archaeological and paleontological sites. Critical interpretations of when humans started eating meat and animal fat or when they started using...
Fossils Bone and Bones Archaeology Animals Deep Learning Humans
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Inferring locomotor behaviours in Miocene New World monkeys using finite element analysis, geometric morphometrics and machine-learning classification techniques applied to talar morphology.

Journal of the Royal Society, Interface Sep 26, 2018
The talus is one of the most commonly preserved post-cranial elements in the platyrrhine fossil record. Talar morphology can provide information about postural adaptations because it is the anatomical structure responsible for transmitting body mass ...
Machine Learning Algorithms Animals Phylogeny Biomechanical Phenomena Biological Evolution Finite Element Analysis Locomotion Fossils Skull Mathematics Talus Models, Anatomic Platyrrhini
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Predictive pollen-based biome modeling using machine learning.

PloS one Aug 23, 2018
This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published Af...
Statistics, Nonparametric Supervised Machine Learning Pollen Support Vector Machine Ecosystem Neural Networks, Computer Bayes Theorem Climate Change Decision Trees Fossils Models, Statistical Africa Algorithms Discriminant Analysis Logistic Models
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Distinguishing butchery cut marks from crocodile bite marks through machine learning methods.

Scientific reports Apr 10, 2018
All models of evolution of human behaviour depend on the correct identification and interpretation of bone surface modifications (BSM) on archaeofaunal assemblages. Crucial evolutionary features, such as the origin of stone tool use, meat-eating, foo...
Bites and Stings Hominidae Tool Use Behavior Fossils Alligators and Crocodiles Computational Biology Bone and Bones Machine Learning Archaeology Animals
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Text-mined fossil biodiversity dynamics using machine learning.

Proceedings. Biological sciences Apr 24, 2019
Documented occurrences of fossil taxa are the empirical foundation for understanding large-scale biodiversity changes and evolutionary dynamics in deep time. The fossil record contains vast amounts of understudied taxa. Yet the compilation of huge vo...
Fossils Bryozoa Data Mining Biological Evolution Machine Learning Animals Paleontology Biodiversity
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