Train and host a computer vision model for tampering detection on Amazon SageMaker: Part 2

This article explains how to develop, train, and deploy a computer vision model on Amazon SageMaker for detecting document tampering in mortgage underwriting.

Specifically, the article covers:

• Overview of the image forgery detection solution using Error Level Analysis (ELA) technique
• Setting up the model training notebook on SageMaker Studio
• Preparing the dataset of original and tampered images
• Preprocessing images using ELA to generate training data
• Configuring and training a CNN model for forgery detection
• Saving and evaluating the trained model
• Setting up the model deployment notebook
• Creating an S3 bucket and uploading model artifacts
• Creating and testing a SageMaker inference endpoint
• Limitations of the ELA technique
• Cleaning up resources