mlsanityData to 7 Oct 2026

The Platform for non-metallic pipes defects recognition. Design and Implementation

arXiv 2212.04706 ↗First posted 9 Dec 2022cs.LGcited by 0

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Abstract (arXiv)

This paper describes a prototype software and hardware platform to provide support to field operators during the inspection of surface defects of non-metallic pipes. Inspection is carried out by video filming defects created on the same surface in real-time using a "smart" helmet device and other mobile devices. The work focuses on the detection and recognition of the defects which appears as colored iridescence of reflected light caused by the diffraction effect arising from the presence of internal stresses in the inspected material. The platform allows you to carry out preliminary analysis directly on the device in offline mode, and, if a connection to the network is established, the received data is transmitted to the server for post-processing to extract information about possible defects that were not detected at the previous stage. The paper presents a description of the stages of design, formal description, and implementation details of the platform. It also provides descriptions of the models used to recognize defects and examples of the result of the work.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 29 references that are in the map. First posted on arXiv 9 Dec 2022.

Builds on

6 of 29 references.

References · 6

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  2. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  3. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  4. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  5. 2016YOLO9000: Better, Faster, Strongercited by 1,429
  6. 2018Object detection at 200 Frames Per Secondcited by 5

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