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  1. Islam KT, Raj RG, Shamsul Islam SM, Wijewickrema S, Hossain MS, Razmovski T, et al.
    Sensors (Basel), 2020 Jun 24;20(12).
    PMID: 32599883 DOI: 10.3390/s20123578
    Automatic vehicle license plate recognition is an essential part of intelligent vehicle access control and monitoring systems. With the increasing number of vehicles, it is important that an effective real-time system for automated license plate recognition is developed. Computer vision techniques are typically used for this task. However, it remains a challenging problem, as both high accuracy and low processing time are required in such a system. Here, we propose a method for license plate recognition that seeks to find a balance between these two requirements. The proposed method consists of two stages: detection and recognition. In the detection stage, the image is processed so that a region of interest is identified. In the recognition stage, features are extracted from the region of interest using the histogram of oriented gradients method. These features are then used to train an artificial neural network to identify characters in the license plate. Experimental results show that the proposed method achieves a high level of accuracy as well as low processing time when compared to existing methods, indicating that it is suitable for real-time applications.
  2. Bester C, Collins A, Razmovski T, Weder S, Briggs RJ, Wei B, et al.
    Hear Res, 2022 Dec;426:108353.
    PMID: 34600798 DOI: 10.1016/j.heares.2021.108353
    BACKGROUND: Preservation of natural hearing during cochlear implantation is associated with improved speech outcomes, however more than half of implant recipients lose this hearing. Real-time electrophysiological monitoring of cochlear output during implantation, made possible by recording electrocochleography using the electrodes on the cochlear implant, has shown promise in predicting hearing preservation. Sudden drops in the amplitude of the cochlear microphonic (CM) have been shown to predict more severe hearing losses. Here, we report on a randomized clinical trial investigating whether immediate surgical intervention triggered by these drops can save residual hearing.

    METHODS: A single-blinded placebo-controlled trial of surgical intervention triggered when CM amplitude dropped by at least 30% of a prior maximum amplitude during cochlear implantation. Intraoperative electrocochleography was recorded in 60 adults implanted with Cochlear Ltd's Thin Straight Electrode, half randomly assigned to a control group and half to an interventional group. The surgical intervention was to withdraw the electrode in ½-mm steps to recover CM amplitude. The primary outcome was hearing preservation 3 months following implantation, with secondary outcomes of speech-in-noise reception thresholds by group or CM outcome, and depth of implantation.

    RESULTS: Sixty patients were recruited; neither pre-operative audiometry nor speech reception thresholds were significantly different between groups. Post-operatively, hearing preservation was significantly better in the interventional group. This was the case in absolute difference (median of 30 dB for control, 20 dB for interventional, χ² = 6.2, p = .013), as well as for relative difference (medians of 66% for the control, 31% for the interventional, χ² = 5.9, p = .015). Speech-in-noise reception thresholds were significantly better in patients with no CM drop at any point during insertion compared with patients with a CM drop; however, those with successfully recovered CMs after an initial drop were not significantly different (median gain required for speech reception score of 50% above noise of 6.9 dB for no drop, 8.6 for recovered CM, and 9.8 for CM drop, χ² = 6.8, p = .032). Angular insertion depth was not significantly different between control and interventional groups.

    CONCLUSIONS: This is the first demonstration that surgical intervention in response to intraoperative hearing monitoring can save residual hearing during cochlear implantation.

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