Real–Time Semantic Segmentation for Railway Anomalies Analysis

Stanik, Paul III; Morris, Brendan; University of Nevada, Las Vegas; University of Nevada. University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability

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Real–Time Semantic Segmentation for Railway Anomalies Analysis

2022-12-01
By Stanik, Paul III ; Morris, Brendan

[PDF-2.07 MB]

English

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Creators:

Stanik, Paul III ; Morris, Brendan

Stanik, Paul III ; Morris, Brendan Less -
Corporate Creators:

University of Nevada, Las Vegas ; University of Nevada. University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability

University of Nevada, Las Vegas ; University of Nevada. University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Computer Vision Costs Inspection Inspection Equipment Maintenance Of Way Performance Video Cameras
Publication/ Report Number:

UNLV-8
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

University of Nevada. University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability
Abstract:

In the past few years, computer vision has made huge jumps due to deep learning which leverages increased computational power and access to data. The computer vision community has also embraced transparency to accelerate research progress by sharing open datasets and open source code. Access to large scale datasets and bench- mark challenges propelled and opened the field. The autonomous vehicle community is a prime example.
Format:

PDF
Funding:

69A3551747132
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha-512:d730bdc137e50ffe55a72dc34ffed224055beea35a007e0f1709657532245ca645cb1db0985199cbd00d0d6900f629e7d0ac702a2656fca87967a264b9189a3d
Download URL:

https://rosap.ntl.bts.gov/view/dot/78334/dot_78334_DS1.pdf
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Real–Time Semantic Segmentation for Railway Anomalies Analysis

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