Backed by Research

Our technology is based on cutting-edge research focused on creating lightweight AI models that outperform traditional heavy networks like ResNet on glaucoma diagnosis — while requiring far fewer resources.

Key Publications

• Energy Efficient Learning Algorithms for Glaucoma Diagnosis — Published in IEEE Xplore
  https://doi.org/10.1109/ICMLA58977.2023.00307
• GAN-based Data Augmentation for Advanced Glaucoma Diagnostics — Featured in Recent Advances in Deep Learning Applications
  https://www.taylorfrancis.com/books/edit/10.1201/9781003570882

Presentations

Our work has been presented at leading scientific conferences, including:

• MIT Undergraduate Research Technology Conference
• IEEE ICMLA 2023