Publications in collaboration with researchers from Universidad CEU San Pablo (12)

2024

  1. A hybrid cascade-parallel discriminative-generative model for pipeline integrity threat detection in a smart fiber optic surveillance system

    Multimedia Tools and Applications

2023

  1. Corrections: Improved perturbation detection in direct detected ϕ-OTDR systems using matched filtering (IEEE Photonics Technology Letters (2019) 31 (1689-1692) DOI: 10.1109/LPT.2019.2940297)

    IEEE Photonics Technology Letters

  2. Corrigendum to “Undiscovered issues and solutions for direct detected Φ-OTDR systems” [Opt. Fiber Technol. 60 (2020) 102346:1–102346:13/102346] (Optical Fiber Technology (2020) 60, (S1068520020303369), (10.1016/j.yofte.2020.102346))

    Optical Fiber Technology

  3. Differentiating trace-to-trace noise effects using novel signal characteristics in phase-sensitive OTDR systems

    Optical and Quantum Electronics, Vol. 55, Núm. 1

2020

  1. Segregating the true perturbation position from ghost energy points region in φ-OTDR systems

    Optics Express, Vol. 28, Núm. 3, pp. 2699-2713

  2. Undiscovered issues and solutions for direct detected ϕ-OTDR systems

    Optical Fiber Technology, Vol. 60

2019

  1. A Contextual GMM-HMM Smart Fiber Optic Surveillance System for Pipeline Integrity Threat Detection

    Journal of Lightwave Technology, Vol. 37, Núm. 18, pp. 4514-4522

  2. Improved Perturbation Detection in Direct Detected φ-OTDR Systems using Matched Filtering

    IEEE Photonics Technology Letters, Vol. 31, Núm. 21, pp. 1689-1692

2018

  1. A Gaussian Mixture Model-Hidden Markov Model (GMM-HMM)-based fiber optic surveillance system for pipeline integrity threat detection

    Optics InfoBase Conference Papers

  2. Real Field Deployment of a Smart Fiber-Optic Surveillance System for Pipeline Integrity Threat Detection: Architectural Issues and Blind Field Test Results

    Journal of Lightwave Technology, Vol. 36, Núm. 4, pp. 1052-1062

2017

  1. A novel fiber optic based surveillance system for prevention of pipeline integrity threats

    Sensors (Switzerland), Vol. 17, Núm. 2

  2. Machine learning methods for pipeline surveillance systems based on distributed acoustic sensing: A review

    Applied Sciences (Switzerland), Vol. 7, Núm. 8