The paradox of predictability provides a bridge between micro-and macroevolution
The relationship between the evolutionary dynamics observed in contemporary populations
(microevolution) and evolution on timescales of millions of years (macroevolution) has been …
(microevolution) and evolution on timescales of millions of years (macroevolution) has been …
Opportunities and challenges in applying AI to evolutionary morphology
Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the
study of evolutionary morphology. While classical AI methods such as principal component …
study of evolutionary morphology. While classical AI methods such as principal component …
Ostracod-based transfer function shifting to a broad prospect in palaeolimnology and palaeoclimate
C Wang, D Zhao, Z Zhou, C Yuan - Science of The Total Environment, 2025 - Elsevier
The ostracod-based transfer function is a common method in palaeolimnology and
palaeoclimate research, serving as an interpreter from fossil record to palaeoenvironment …
palaeoclimate research, serving as an interpreter from fossil record to palaeoenvironment …
Accelerating segmentation of fossil CT scans through Deep Learning
EM Knutsen, DA Konovalov - Scientific Reports, 2024 - nature.com
Abstract Recent developments in Deep Learning have opened the possibility for automated
segmentation of large and highly detailed CT scan datasets of fossil material. However …
segmentation of large and highly detailed CT scan datasets of fossil material. However …
Artificial Intelligence-powered fossil shark tooth identification: Unleashing the potential of Convolutional Neural Networks
All fields of knowledge are being impacted by Artificial Intelligence. In particular, the Deep
Learning paradigm enables the development of data analysis tools that support subject …
Learning paradigm enables the development of data analysis tools that support subject …
[PDF][PDF] An explainable Convolutional Neural Network approach to fossil shark tooth identification
This study explores the capability of Convolutional Neural Networks (CNNs), a particular
class of Deep Learning algorithms specifically crafted for computer vision tasks, to classify …
class of Deep Learning algorithms specifically crafted for computer vision tasks, to classify …
Automatic Segmentation of Early Triassic Vertebrate Fossil CT Scans: Reducing Human Annotation Time through Deep Learning
EM Knutsen, DA Konovalov - 2024 - researchsquare.com
Abstract Recent developments in Deep Learning have opened the possibility for automated
segmentation of large and highly detailed CT scan datasets of fossil material. However …
segmentation of large and highly detailed CT scan datasets of fossil material. However …
[PDF][PDF] Integrative Organismal Biology
Y He, JM Mulqueeney, EC Watt, A Salili-James… - 2024 - researchgate.net
Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the
study of evolutionary morphology. While classical AI methods such as principal component …
study of evolutionary morphology. While classical AI methods such as principal component …
[PDF][PDF] Tsuboi, M, Sztepanacz, J, De Lisle, S, Voje, KL, Grabowski, M, Hopkins, MJ, Porto, A, Balk, M, Pontarp, M, Rossoni, D, Hildesheim, LS, Horta-Lacueva, QJ-B …
M Tsuboi - researchonline.ljmu.ac.uk
The relationship between the evolutionary dynamics observed in contemporary populations
(microevolution) and evolution on timescales of millions of years (macroevolution) has been …
(microevolution) and evolution on timescales of millions of years (macroevolution) has been …