Deep learning as a tool for ecology and evolution
Deep learning is driving recent advances behind many everyday technologies, including
speech and image recognition, natural language processing and autonomous driving. It is …
speech and image recognition, natural language processing and autonomous driving. It is …
Taxonomic review of living planktonic foraminifera
GJA Brummer, M Kučera - Journal of Micropalaeontology, 2022 - jm.copernicus.org
Applications of fossil shells of planktonic foraminifera to decipher past environmental
change and plankton evolution require a robust operational taxonomy. In this respect, extant …
change and plankton evolution require a robust operational taxonomy. In this respect, extant …
Using the fossil record to understand extinction risk and inform marine conservation in a changing world
Understanding the long-term effects of ongoing global environmental change on marine
ecosystems requires a cross-disciplinary approach. Deep-time and recent fossil records can …
ecosystems requires a cross-disciplinary approach. Deep-time and recent fossil records can …
Quantifying the effect of anthropogenic climate change on calcifying plankton
Widely regarded as an imminent threat to our oceans, ocean acidification has been
documented in all oceanic basins. Projected changes in seawater chemistry will have …
documented in all oceanic basins. Projected changes in seawater chemistry will have …
[HTML][HTML] Zircon classification from cathodoluminescence images using deep learning
Zircon is a widely-used heavy mineral in geochronological and geochemical research
because it can extract important information to understand the history and genesis of rocks …
because it can extract important information to understand the history and genesis of rocks …
Automated analysis of foraminifera fossil records by image classification using a convolutional neural network
Manual identification of foraminiferal morphospecies or morphotypes under stereo
microscopes is time consuming for micropalaeontologists and not possible for …
microscopes is time consuming for micropalaeontologists and not possible for …
Automatic taxonomic identification based on the Fossil Image Dataset (> 415,000 images) and deep convolutional neural networks
The rapid and accurate taxonomic identification of fossils is of great significance in
paleontology, biostratigraphy, and other fields. However, taxonomic identification is often …
paleontology, biostratigraphy, and other fields. However, taxonomic identification is often …
Automatic identification of fossils and abiotic grains during carbonate microfacies analysis using deep convolutional neural networks
Petrographic analysis based on microfacies identification in thin sections is widely used in
sedimentary environment interpretation and paleoecological reconstruction. Fossil …
sedimentary environment interpretation and paleoecological reconstruction. Fossil …
[HTML][HTML] Artificial intelligence in paleontology
The accumulation of large datasets and increasing data availability have led to the
emergence of data-driven paleontological studies, which reveal an unprecedented picture of …
emergence of data-driven paleontological studies, which reveal an unprecedented picture of …
Species-level microfossil identification for globotruncana genus using hybrid deep learning algorithms from the scratch via a low-cost light microscope imaging
Paleontologists generally use a low-cost electro-optical system to classify microfossils. This
manual identification is a time-consuming process and it may take about a long time …
manual identification is a time-consuming process and it may take about a long time …