Results 1 to 9 of about 9 (9)

Environmental Metal Pollution Considered as Noise: Effects on the Spatial Distribution of Benthic Foraminifera in two Coastal Marine Areas of Sicily (Southern Italy) [PDF]

open access: yesEcological Modelling, Vol. 213, 449 - 462 (2008), 2008
We analyze the spatial distributions of two groups of benthic foraminifera (Adelosina spp. + Quinqueloculina spp. and Elphidium spp.), along Sicilian coast, and their correlation with six different heavy metals, responsible for the pollution. Samples were collected inside the Gulf of Palermo, which has a high level of pollution due to heavy metals, and
arxiv   +1 more source

Instance Segmentation of Microscopic Foraminifera [PDF]

open access: yesarXiv, 2021
Foraminifera are single-celled marine organisms that construct shells that remain as fossils in the marine sediments. Classifying and counting these fossils are important in e.g. paleo-oceanographic and -climatological research. However, the identification and counting process has been performed manually since the 1800s and is laborious and time ...
arxiv  

ForamViT-GAN: Exploring New Paradigms in Deep Learning for Micropaleontological Image Analysis [PDF]

open access: yesarXiv, 2023
Micropaleontology in geosciences focuses on studying the evolution of microfossils (e.g., foraminifera) through geological records to reconstruct past environmental and climatic conditions. This field heavily relies on visual recognition of microfossil features, making it suitable for computer vision technology, specifically deep convolutional neural ...
arxiv  

Visual Microfossil Identification via Deep Metric Learning [PDF]

open access: yesarXiv, 2021
We apply deep metric learning for the first time to the problem of classifying planktic foraminifer shells on microscopic images. This species recognition task is an important information source and scientific pillar for reconstructing past climates.
arxiv  

A Bayesian Hierarchical Model for Reconstructing Sea Levels: From Raw Data to Rates of Change [PDF]

open access: yes, 2015
We present a holistic Bayesian hierarchical model for reconstructing the continuous and dynamic evolution of relative sea-level (RSL) change with fully quantified uncertainty. The reconstruction is produced from biological (foraminifera) and geochemical ({\delta}13C) sea-level indicators preserved in dated cores of salt-marsh sediment.
arxiv   +1 more source

Towards detection and classification of microscopic foraminifera using transfer learning [PDF]

open access: yesarXiv, 2020
Foraminifera are single-celled marine organisms, which may have a planktic or benthic lifestyle. During their life cycle they construct shells consisting of one or more chambers, and these shells remain as fossils in marine sediments. Classifying and counting these fossils have become an important tool in e.g. oceanography and climatology.
arxiv  

Cyclic Fluctuations, Climatic Changes and Role of Noise in Planktonic Foraminifera in the Mediterranean Sea [PDF]

open access: yesPublished in Fluct. Noise Lett. Vol. 5, L349-L355 (2005), 2005
The study of Planktonic Foraminifera abundances permits to obtain climatic curves on the basis of percentage ratio between tropical and temperate/polar forms. Climatic changes were controlled by several phenomena as: (i) Milankovitch's cycles, produced by variations of astronomical parameters such as precession, obliquity and eccentricity; (ii ...
arxiv  

Estimating breakpoints between climate states in the Cenozoic Era [PDF]

open access: yesarXiv
This study presents a statistical time-domain approach for identifying transitions between climate states, referred to as breakpoints, using well-established econometric tools. We analyze a 67.1 million year record of the oxygen isotope ratio delta-O-18 derived from benthic foraminifera. The dataset is presented in Westerhold et al.
arxiv  

Continuous-time state-space methods for delta-O-18 and delta-C-13 [PDF]

open access: yesarXiv
Time series analysis of delta-O-18 and delta-C-13 measurements from benthic foraminifera for purposes of paleoclimatology is challenging. The time series reach back tens of millions of years, they are relatively sparse in the early record and relatively dense in the later, the time stamps of the observations are not evenly spaced, and there are ...
arxiv  
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