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Machine Learning & Computer Vision Consulting Services 2025

USARFP notice for Machine Learning & Computer Vision Consulting Services 2025. The reference ID of the tender is 127130686 and it is closing on 24 Oct 2025.

Tender Details

  • Country: USA
  • Summary: Machine Learning & Computer Vision Consulting Services 2025
  • UST Ref No: 127130686
  • Deadline: 24 Oct 2025
  • Financier: Self Financed
  • Purchaser Ownership: Government
  • Tender Value: Refer Document
  • Notice Type: Tender
  • Document Ref. No.:
  • Purchaser's Detail:
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  • Description:
  • The Vermont Agency of Transportation (VTrans) is seeking consultant services to carry out the extraction of roadway roadside feature data elements using computer vision and machine learning modeling applied to existing video log imagery. This project will support the collection and assessment of data related to rigid objects, side slopes, clear zones and guardrails along rural U.S. and Vermont roadways. This comprehensive dataset will enhance risk-based analysis and data-driven decision-making to guide targeted infrastructure safety improvements. To perform this project, a service provider should have demonstrated expertise in machine learning and computer vision and have access to high performance computing to run models using a large number of images.
  • Documents:

 Tender Notice

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Machine Learning & Computer Vision Consulting Services 2025 - USA Tender

The AGENCY OF TRANSPORTATION - CONTRACT ADMINISTRATION, a Government sector organization in USA, has announced a new tender for Machine Learning & Computer Vision Consulting Services 2025. This tender is published on USARFP under UST Ref No: 127130686 and is categorized as a Tender. Interested and eligible suppliers are invited to participate by reviewing the tender documents and submitting their bids before the deadline on 2025-10-24.

The estimated tender value is Refer Document, and full details, including technical specifications and submission requirements, are provided in the official tender documents. Ensure all submissions meet the criteria outlined to be considered for evaluation.

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