International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
November-December 2024

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

AI Applications in Palaeontology: Enhancing Fossil Analysis and Interpretation

Author(s) Nethravathi B, Sudarshan J S, Bhargava Sharma C S, Ashish Kumar Mishra
Country India
Abstract The proliferation of large datasets has facilitated data-driven approaches in paleontology, offering novel insights into evolutionary history. However, managing complex data poses challenges, including laborious processing and a lack of standardized evaluation metrics. Despite the widespread use of artificial intelligence (AI) in other scientific domains, its adoption in paleontology remains limited. This study reviews over 70 AI studies in paleontology since the 1980s, encompassing tasks such as micro- and macrofossil classification, image segmentation, and prediction. Various machine learning solutions, including Knowledge-Based Systems have been employed to automate paleontological workflows. The rise in AI adoption is attributed primarily to improved accessibility rather than advancements in fossil data or methodologies. Additionally, emerging AI implementations like diffusion models and the potential for Large Language Models is evident for future integration with paleontological research. Although AI has yet to become integral to paleontologists' toolkits, its successful implementation suggests transformative prospects for the field.
Keywords Microfossils, Artificial intelligence, data-driven paleontology, machine learning.
Field Engineering
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-10
Cite This AI Applications in Palaeontology: Enhancing Fossil Analysis and Interpretation - Nethravathi B, Sudarshan J S, Bhargava Sharma C S, Ashish Kumar Mishra - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32770
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.32770
Short DOI https://doi.org/g8vggk
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5Cover Page Vol 6 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-5948-55 editor@ijfmr.com