Dinosaur footprints automated detection with deep learning + iInvertebrate ichnofossils and dinosaur undertracks from Middle Jurassic of Morocco
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Ben Creisler
Jun 4, 2026, 4:02:58 PM (2 days ago) Jun 4
to DinosaurMa...@googlegroups.com
Ben Creisler
New papers;
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Yeoncheol Ha & Seung-Sep Kim (2026)
Deep learning enables automated detection of dinosaur footprints with high accuracy
Scientific Reports (advance online publication)
https://doi.org/10.1038/s41598-026-56031-5
https://link.springer.com/article/10.1038/s41598-026-56031-5
Dinosaur footprints provide crucial paleoecological information about locomotion, behavior, and tracksite distributions. Traditional tracksite surveys rely on time-consuming manual identification by expert researchers, with results influenced by preservation quality and subjective interpretation. Here, we present an automated detection system for dinosaur footprints using You Only Look Once version 8 (YOLOv8), an effective object detection neural network. We trained the model on 49,242 images from the AI-Hub dataset, comprising theropod, ornithopod, and sauropod footprints from Korean tracksites. The final model achieved a mean average precision (mAP50) of 0.949 and mAP50-95 of 0.660. To address resolution-dependent detection challenges, we developed a multi-scale detection approach combining predictions across eight different image resolutions. Testing on previously unseen tracksites demonstrated successful detection of footprints from both Korea and Brazil, including the ichnospecies Farlowichnus rapidus, indicating strong cross-regional generalization. Our results show that detection accuracy depends on illumination conditions, preservation quality, and the presence of outline markings. This deep learning approach offers an efficient alternative to manual tracksite exploration, enabling rapid spatial distribution mapping of extensive dinosaur tracksites while providing objective, reproducible detection results.
Yeoncheol Ha & Seung-Sep Kim (2026)
Deep learning enables automated detection of dinosaur footprints with high accuracy
Scientific Reports (advance online publication)
https://doi.org/10.1038/s41598-026-56031-5
https://link.springer.com/article/10.1038/s41598-026-56031-5
Dinosaur footprints provide crucial paleoecological information about locomotion, behavior, and tracksite distributions. Traditional tracksite surveys rely on time-consuming manual identification by expert researchers, with results influenced by preservation quality and subjective interpretation. Here, we present an automated detection system for dinosaur footprints using You Only Look Once version 8 (YOLOv8), an effective object detection neural network. We trained the model on 49,242 images from the AI-Hub dataset, comprising theropod, ornithopod, and sauropod footprints from Korean tracksites. The final model achieved a mean average precision (mAP50) of 0.949 and mAP50-95 of 0.660. To address resolution-dependent detection challenges, we developed a multi-scale detection approach combining predictions across eight different image resolutions. Testing on previously unseen tracksites demonstrated successful detection of footprints from both Korea and Brazil, including the ichnospecies Farlowichnus rapidus, indicating strong cross-regional generalization. Our results show that detection accuracy depends on illumination conditions, preservation quality, and the presence of outline markings. This deep learning approach offers an efficient alternative to manual tracksite exploration, enabling rapid spatial distribution mapping of extensive dinosaur tracksites while providing objective, reproducible detection results.
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Mohamed El Ouali, Badre Essafraoui, Lahcen Kabiri, Laila El-Ouali, Mohamed Abioui & Olev Vinn (2026)
Invertebrate ichnofossils and dinosaur undertracks from the Middle Jurassic of Tizi N’Talghemt area, Central High Atlas, Morocco
Palaeoworld 201139
doi: https://doi.org/10.1016/j.palwor.2026.201139
https://www.sciencedirect.com/science/article/abs/pii/S1871174X26000740
Trace fossils, or ichnofossils, serve as records of biological activity and provide critical insights into past sedimentary environments. This study aims to fill the gap in ichnological research on carbonate environments in the Moroccan Central High Atlas by describing and analyzing invertebrate trace fossils and dinosaur undertracks from the Middle Jurassic of the Tizi N’Talghemt area in Morocco. The Moroccan Central High Atlas is characterized by syncline basins with Jurassic carbonate deposits. Fieldwork conducted in 2023 documented a 470 m stratigraphic section, focusing on the Tillouguit and Guettioua formations. The ichnological analysis identified several trace fossils, including those attributed to Eubrontes and Dinehichnus, offering insights into the presence and behavior of theropods and ornithopods in the region during the Bathonian–Callovian period. The Thalassinoides burrows suggest well-oxygenated, nutrient-rich conditions, while the Rhizocorallium burrows are not useful indicators of paleoenvironment. Paleoenvironmental analysis suggests that late Bajocian sedimentation likely occurred in shallow marine conditions, transitioning to deltaic environments by the Bathonian–Callovian. The presence of dinosaur tracks on tidal flats during low tide points to significant ecological interactions, potentially including predator-prey relationships between theropods and ornithopods though not established via direct evidence. This study not only contributes to the understanding of the ichnology of Moroccan Jurassic sediments but also provides valuable proxy for reconstructing the paleoenvironment for paleoecological and sedimentological conditions. The findings underscore the significance of integrating ichnological data with stratigraphic and sedimentological studies to enhance our understanding of ancient ecosystems.
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Invertebrate ichnofossils and dinosaur undertracks from the Middle Jurassic of Tizi N’Talghemt area, Central High Atlas, Morocco
Palaeoworld 201139
doi: https://doi.org/10.1016/j.palwor.2026.201139
https://www.sciencedirect.com/science/article/abs/pii/S1871174X26000740
Trace fossils, or ichnofossils, serve as records of biological activity and provide critical insights into past sedimentary environments. This study aims to fill the gap in ichnological research on carbonate environments in the Moroccan Central High Atlas by describing and analyzing invertebrate trace fossils and dinosaur undertracks from the Middle Jurassic of the Tizi N’Talghemt area in Morocco. The Moroccan Central High Atlas is characterized by syncline basins with Jurassic carbonate deposits. Fieldwork conducted in 2023 documented a 470 m stratigraphic section, focusing on the Tillouguit and Guettioua formations. The ichnological analysis identified several trace fossils, including those attributed to Eubrontes and Dinehichnus, offering insights into the presence and behavior of theropods and ornithopods in the region during the Bathonian–Callovian period. The Thalassinoides burrows suggest well-oxygenated, nutrient-rich conditions, while the Rhizocorallium burrows are not useful indicators of paleoenvironment. Paleoenvironmental analysis suggests that late Bajocian sedimentation likely occurred in shallow marine conditions, transitioning to deltaic environments by the Bathonian–Callovian. The presence of dinosaur tracks on tidal flats during low tide points to significant ecological interactions, potentially including predator-prey relationships between theropods and ornithopods though not established via direct evidence. This study not only contributes to the understanding of the ichnology of Moroccan Jurassic sediments but also provides valuable proxy for reconstructing the paleoenvironment for paleoecological and sedimentological conditions. The findings underscore the significance of integrating ichnological data with stratigraphic and sedimentological studies to enhance our understanding of ancient ecosystems.
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