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Author: search.filters.author.Assawaroongsakul, PongpolHas files: No

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    Breast Cancer Detection using IR-UWB with Deep Learning
    (2021-01-01)
    Khumdee, Mawin
    ;
    Assawaroongsakul, Pongpol
    ;
    Phasukkit, Pattarapong
    ;
    Houngkamhang, Nongluck
    This paper proposes breast cancer positioning detection using the IR-UWB system with deep learning, which is an interesting alternative method. When compared to ultrasound, x-ray mammogram, and CT-scan, there are several advantages to using IR-UWB, including low cost, less energy required, less long-term effect, portability, and providing much more breast cancer screening access for patients. Nowadays, the IR-UWB system has many techniques for processing IR-UWB signals, and one of the most interesting technique is using deep learning. In this study, we collected data from nine IR-UWB antennas. Then, the prepared data is fed through Deep Neural Networks to find the hidden patterns of signal and predict the cancer position which are 16 of breast cancer positions and one of undetected, also known as 17 classes. The model gave an average accuracy up to 95.60%.
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    Deep Learning-Based Human Recognition Through the Wall using UWB radar
    (2021-01-01)
    Assawaroongsakul, Pongpol
    ;
    Khumdee, Mawin
    ;
    Phasukkit, Pattarapong
    ;
    Houngkamhang, Nongluck
    Human activity detection in obscured or invisible area, for instance, human detection through the wall has become an interesting topic because it has potential for security, rescue, activity analysis application, etc. UWB radar, a detection system produces short radio frequency pulses and measures the reflected signals which UWB pulses have high spatial resolution and enable penetration in dielectric materials, was used to collect human activity through the wall signals at the frequency range of 3 GHz in this research. Subsequently, we applied signal data with the Deep Neural Network model to classify 5 classes of human activity including standing, walking, sitting, laying, and no-human gave the F1 score up to 96.94%.