Location
Presentation- Allen E. Paulson College of Engineering and Computing
Document Type and Release Option
Thesis Presentation (Restricted to Georgia Southern)
Faculty Mentor
Rami Haddad
Faculty Mentor Email
rhaddad@georgiasouthern.edu
Presentation Year
2021
Start Date
26-4-2021 12:00 AM
End Date
30-4-2021 12:00 AM
Keywords
Machine learning, datasets
Description
Modern machine learning problems require vast amounts of data to train and achieve optimal performance. Currently, the availability of data is highly reliant upon the previous existence of curated datasets or a strenuous collection process. This stifles research into innovative machine learning applications and often disproportionally affects smaller and less well-funded research teams. To address these concerns, a tool is proposed to help automate the image collection process. Composed of a graphical user interface and an adaptive network training scheme, the tool will expand access to large, individualized datasets for smaller and more inexperienced teams.
Academic Unit
Allen E. Paulson College of Engineering and Computing
Automated Image Dataset Creation via Machine Learning
Presentation- Allen E. Paulson College of Engineering and Computing
Modern machine learning problems require vast amounts of data to train and achieve optimal performance. Currently, the availability of data is highly reliant upon the previous existence of curated datasets or a strenuous collection process. This stifles research into innovative machine learning applications and often disproportionally affects smaller and less well-funded research teams. To address these concerns, a tool is proposed to help automate the image collection process. Composed of a graphical user interface and an adaptive network training scheme, the tool will expand access to large, individualized datasets for smaller and more inexperienced teams.
Comments
This work is archived and distributed under the repository's standard copyright and reuse license, available here. Under this license, end-users may copy, store, and distribute this work without restriction. For questions related to additional reuse of this work, please contact the copyright owner.