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

• Published in: IEEE access Vol. 11; pp. 67298 - 67307
• Main Authors: Ferreira-Chacua, Ivan, Koeshidayatullah, Ardiansyah Ibnu
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Availability; Classification; Computer architecture; Computer vision; Datasets; Deep learning; few-shot learning; foraminifera; Fossils; GAN; Generative adversarial networks; Geology; High resolution; Image analysis; Image quality; Image resolution; Image segmentation; Machine learning; Microorganisms; Paleontology; Semantic segmentation; Semantics; Signal to noise ratio; Superresolution; Synthetic data; Training; transformer; Transformers; Visual tasks; Workflow

In geosciences, micropaleontology studies the evolution of microfossils (e.g., foraminifera) throughout geological records and utilizes such information to reconstruct past environmental and climatic conditions. This field depends primarily on the visual recognition of various features in microfossi...