CorrSave
Corrosion Images Classification to Improve Industrial Corrosion Management
Author:
1. WQD180122 - Nur Afiqah Zainol Abidin
2. WQD180079 - Sidratul Muntaha
3. WQD180088 - Lai Kah Yeen
4. WQD180119 - Lee Zhao Wei
Date: May 30 2019
INTRODUCTION
BRIEF DESCRIPTION OF PROJECT
Create a Shiny App that presents a classification of corroded materials using machine learning techniques and features trained from a model as an alternative solution for better industrial corrosion management in organizations that uses metallic machines & equipments on a daily basis.
GOAL
Train a model to differentiate between corroded and non-corroded surfaces in the form of images.
DATASET?
Dataset 1: Owned pre-trained images (Zoomed in images from Google) Dataset 2: Clients' images for training
PROJECT INPUT
PROJECT OUTPUT
CONCLUSION
EXPERIENCES EARNED
- Learn new things
- To create data product using Shiny App
- To customize RStudio Presenter
- To develop marketable data product
- Image Processing Features