Mobile oral cancer image classification based on efficient deep learning for low-resource settings

Bofan Song, Sumsum Sunny, Shaobai Li, G. Keerthi, Sanjana Patrick, Nirza Mukhia, Shubha Gurudath, Subhashini Raghavan, Pramila Mendonca, Tsusennaro, Shirley T. Leivon, Trupti Kolur, Vivek Shetty, R. Vidya Bushan, Rohan Ramesh, Vijay Pillai, Alben Sigamani, Amritha Suresh, moni Abraham Kuriakose, Praveen BirurRongguang Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We will report a mobile-based dual-mode image classification method for oral cancer detection in low-resource settings.

Original languageEnglish (US)
Title of host publicationFrontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020
PublisherThe Optical Society
ISBN (Electronic)9781557528209
DOIs
StatePublished - Sep 14 2020
Event2020 Frontiers in Optics Conference, FiO 2020 - Washington, United States
Duration: Sep 14 2020Sep 17 2020

Publication series

NameOptics InfoBase Conference Papers

Conference

Conference2020 Frontiers in Optics Conference, FiO 2020
CountryUnited States
CityWashington
Period9/14/209/17/20

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint Dive into the research topics of 'Mobile oral cancer image classification based on efficient deep learning for low-resource settings'. Together they form a unique fingerprint.

Cite this