Quantum machine learning for chemistry and physics
Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …
pertinent patterns within a given data set with the objective of subsequent generation of …
Imaging plant cells and organs with light-sheet and super-resolution microscopy
The documentation of plant growth and development requires integrative and scalable
approaches to investigate and spatiotemporally resolve various dynamic processes at …
approaches to investigate and spatiotemporally resolve various dynamic processes at …
Long-tailed recognition via weight balancing
S Alshammari, YX Wang… - Proceedings of the …, 2022 - openaccess.thecvf.com
In the real open world, data tends to follow long-tailed class distributions, motivating the well-
studied long-tailed recognition (LTR) problem. Naive training produces models that are …
studied long-tailed recognition (LTR) problem. Naive training produces models that are …
[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 …
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 …
[HTML][HTML] DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring
M Polling, M Sin, LA de Weger… - Science of the Total …, 2022 - Elsevier
Airborne pollen monitoring is of global socio-economic importance as it provides information
on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has …
on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has …
Machine Learning interspecific identification of mouse first lower molars (genus Mus Linnaeus, 1758) and application to fossil remains from the Estrecho Cave (Spain)
A Moclan, ÁC Domínguez-García, E Stoetzel… - Quaternary Science …, 2023 - Elsevier
One of the first steps to address palaeontological studies is the taxonomic identification of
fossils according to their morphology. Geometric Morphometric techniques together with …
fossils according to their morphology. Geometric Morphometric techniques together with …
Hierarchical multi-label taxonomic classification of carbonate skeletal grains with deep learning
M Ho, S Idgunji, JL Payne, A Koeshidayatullah - Sedimentary Geology, 2023 - Elsevier
Abstract Recent advances in Artificial Intelligence (AI), particularly the rise of deep learning,
are revolutionizing data collection and analysis in many aspects of the Earth Sciences …
are revolutionizing data collection and analysis in many aspects of the Earth Sciences …
Neural networks for increased accuracy of allergenic pollen monitoring
Monitoring of airborne pollen concentrations provides an important source of information for
the globally increasing number of hay fever patients. Airborne pollen is traditionally counted …
the globally increasing number of hay fever patients. Airborne pollen is traditionally counted …
The evolutionary history of the Central Asian steppe-desert taxon Nitraria (Nitrariaceae) as revealed by integration of fossil pollen morphology and molecular data
The transition from a greenhouse to an icehouse world at the Eocene-Oligocene Transition
(EOT) coincided with a large decrease of pollen from the steppe-adapted genus Nitraria …
(EOT) coincided with a large decrease of pollen from the steppe-adapted genus Nitraria …