KEYWORDS: Data modeling, Deep learning, Visual process modeling, Process modeling, Object detection, Machine vision, Project management, Image classification, Artificial intelligence
Deep learning (DL) for machine vision tasks has seen enormous growth and success in recent years. However, the complexity of the DL model development workflow and the prevalence of code-based solutions which are powerful for research but have limited scalability, poses a challenge in managing a large number of DL projects and datasets. In this paper, we propose an integrated platform, named MIMOS Machine Vision Package (MiMVP) Deep Learning. The MiMVP could provide a single, desktop-based visual interface to manage DL projects and guide the user through the workflow of developing and training DL models, from preparing data, training and tuning model, and comparing and analyzing results. By streamlining the DL workflow, this platform can enhance the efficiency of DL model development .
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.