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Deep Learning for Sidewalk Accessibility Awarded 'Best Student Paper' at ASSETS'19

Jon E. Froehlich

By Jon E. Froehlich

Oct 29, 2019

Galen Weld and Jon Froehlich holding the awards

Our ASSETS'19 paper "Deep Learning for Automatically Detecting Sidewalk Accessibility Problems Using Streetscape Imagery" was just recognized with the 'Best Student Paper Award'--given to only one of the 158 submissions

Congrats team!

More About

  • Deep Learning for Sidewalk Assessment

  • Project Sidewalk

  • Jon E. Froehlich

  • Galen Weld

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Makeability Lab

We design, build, and evaluate new interactive tools and techniques to address pressing societal challenges. Makeability refers both to how our technological innovations make new abilities possible for humans as well as our educational mission to help students gain new abilities as they learn and grow through research, invention, and human-centered design.

Recent News

March 12, 2026

Xia Su Passes Generals

March 09, 2026

GeoVisA11y Earns Best Paper at CHI'26

March 05, 2026

Arnavi at Stanford for AI for Accessibility Collective

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Paul G. Allen School of Computer Science & Engineering
University of Washington