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OMB Individually Reported

Automatic Track Change Detection Demonstration and Analysis

Low riskExact public inventory row

Description

Description: DeepCNet-based neural network to identify and classify track-related features (e.g., track components, such as fasteners and ties) for ""change detection"" applications. Input: Line-scan images from rail-bound inspection systems.

Detailed example

Notification of changes from status quo or between different inspections based on geolocation.

AI / analytics pattern

Other

Automation level / stage

a) Pre-deployment – The use case is in a development or acquisition status.

Controls / human review

ATO: N/A; PIA: No

Source

OMB 2025 Federal Agency AI Use Case Inventory

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