Transportation Learning Network

Virtual Learning
CTIPS: An End-to-End Deep Learning System for Pavement Distress Detection, Severity Estimation, and Condition Reporting (CTIPS-051)

  • Date: Oct 29, 2026
    Time: 9:30 - 10:30 am CT; 8:30 - 9:30 am MT
    Delivery: Live Zoom Webinar (desktop/laptop and mobile devices)

Registration

REGISTER HERE

Why Attend

Accurate pavement assessments are critical for effective maintenance and asset management. However, traditional methods can be time-consuming and labor-intensive. This research explores an innovative approach using AI, deep learning, and advanced imaging to automate distress detection, severity estimation, and pavement condition evaluation. The goal is to improve efficiency and deliver clear reports to support informed maintenance and investment decisions.

Interactive Features

  • Engage with presenter and peers via chat or Q&A
  • Live polling / surveys / annotations – varies by presentation
  • Downloadable reference materials

Your Presenter(s)

Armstrong Aboah, PhD is Assistant Professor of Transportation Engineering at North Dakota State University