YSH

Comparative Analysis of ML Models for Street Pothole Detection

OverviewThe ProblemThe SolutionKey OutcomesScreenshots
Comparative Analysis of ML Models for Street Pothole Detection — Research paper comparing CNN, ResNet-50, and Decision Trees

Overview

Research paper comparing CNN, ResNet-50, and Decision Trees

GitHub

The Problem

Civic infrastructure teams need quantitative guidance on which detectors reliably spot potholes from street imagery before deploying expensive repairs.

The Solution

I benchmarked CNNs, ResNet-50, and decision-tree baselines in Python/TensorFlow with rigorous dataset splits, validation protocols, and comparative metrics suited to an academic paper.

Technologies used

PythonTensorFlowCNNResNet-50Machine Learning

Key Outcomes

  • Documented trade-offs between deep models and classical learners on the same corpus.
  • Public GitHub artifact enabling reviewers to reproduce charts and tables.

Screenshots & gallery

Dataset Overview4 images
Model Training & Validation1 image
Results & Analysis3 images