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    Fast Backpropagation Neural Network for VQ-Image Compression by Basil Mahmood, Omaima AL-Allaf

    Published 2004-05-01
    “…Artificial neural networks are becoming very attractive in image processing where high computational performance and parallel architectures are required.…”
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  4. 12444

    Design and Implementation of Distributed Real-time Security System via Mobile Technology by Dhuha Abdullah, Wael Mahmood

    Published 2013-07-01
    “…The designed electronic circuit contains the Microcontroller for reading sensors connected to ports of the building (G1, G2, and G3) and processing the signals. Also, there is a monitoring camera to capture an image when registering a case of breach. …”
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  5. 12445

    Embedded Descriptor Generation in Faster R-CNN for Multi-Object Tracking by Younis Younis, Khalil Alsaif

    Published 2021-12-01
    “…The proposed method is evaluated using the UA-DETRAC (University at Albany Detection and Tracking) dataset and has been able to achieve 64.8% MOTA and 83.6% MOTP, with a processing speed of 127.3 frames per second.…”
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    Unleashing the hidden powers of low-cost IoT boards: GPU-based edutainment case study by Marwa K. Elteir, Shaimaa Lazem, Mohamed Azab

    Published 2022-03-01
    “…Unfortunately, even with the limited energy consumption and high processing power of such GPUs, CPUs are usually the only computational element utilized by the hosted applications, thus hindering the capabilities of the entire board. …”
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    An Inclusive review on deep learning techniques and their scope in handwriting recognition by Sukhdeep Singh, Sudhir Rohilla, Anuj Sharma

    Published 2025-05-01
    “…Nevertheless, the present handwriting recognition survey foresees deep learning enabling changes at both bench and bedside with the potential to transform several domains as image processing, speech recognition, computer vision, machine translation, robotics and control, medical imaging, medical information processing, bio-informatics, natural language processing, cyber security, and many others. …”
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    An end-to-end real-time pollutants spilling recognition in wastewater based on the IoT-ready SENSIPLUS platform by Luca Gerevini, Gianni Cerro, Alessandro Bria, Claudio Marrocco, Luigi Ferrigno, Michele Vitelli, Andrea Ria, Mario Molinara

    Published 2023-01-01
    “…The measurement system, i.e., the sensing part, is represented by the so-called Smart Cable Water based on the SENSIPLUS chip, which integrates an array of sensors detecting various water-soluble substances through impedance spectroscopy. The data processing is based on a commercial Micro Control Unit (MCU), including an anomaly detection module, a classification module, and a false positive reduction module, all based on machine learning algorithms that have a computational complexity suitable for low-cost hardware implementation.An extensive experimental campaign on different contaminants has been carried out to train machine-learning algorithms suitable for low-cost and low-power MCU. …”
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