دانلود مقاله انگلیسی رایگان:تشخیص رفتارهای کلیشه ای برای تشخیص زودهنگام اختلالات طیف اوتیسم با کمک بینایی ماشین - 2021
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  • Vision-assisted recognition of stereotype behaviors for early diagnosis of Autism Spectrum Disorders Vision-assisted recognition of stereotype behaviors for early diagnosis of Autism Spectrum Disorders
    Vision-assisted recognition of stereotype behaviors for early diagnosis of Autism Spectrum Disorders

    سال انتشار:

    2021


    عنوان انگلیسی مقاله:

    Vision-assisted recognition of stereotype behaviors for early diagnosis of Autism Spectrum Disorders


    ترجمه فارسی عنوان مقاله:

    تشخیص رفتارهای کلیشه ای برای تشخیص زودهنگام اختلالات طیف اوتیسم با کمک بینایی ماشین


    منبع:

    Sciencedirect - Elsevier - Neurocomputing, 446 (2021) 145-155: doi:10:1016/j:neucom:2021:03:004


    نویسنده:

    Farhood Negin


    چکیده انگلیسی:

    Medical diagnosis supported by computer-assisted technologies is getting more popularity and acceptance among medical society. In this paper, we propose a non-intrusive vision-assisted method based on human action recognition to facilitate the diagnosis of Autism Spectrum Disorder (ASD). We collected a novel and comprehensive video dataset f the most distinctive Stereotype actions of this disorder with the assistance of professional clinicians. Several frameworks as a function of different input modalities were developed and used to produce extensive baseline results. Various local descriptors, which are commonly used within the Bag-of-Visual-Words approach, were tested with Multi-layer Perceptron (MLP), Gaussian Naive Bayes (GNB), and Support Vector Machines (SVM) classifiers for recognizing ASD associated behaviors. Additionally, we developed a framework that first receives articulated pose-based skeleton sequences as input and follows an LSTM network to learn the temporal evolution of the poses. Finally, obtained results were compared with two fine-tuned deep neural networks: ConvLSTM and 3DCNN. The results revealed that the Histogram of Optical Flow (HOF) descriptor achieves the best results when used with MLP classifier. The promising baseline results also confirmed that an action-recognition-based system can be potentially used to assist clinicians to provide a reliable, accurate, and timely diagnosis of ASD disorder.© 2021 Elsevier B.V. All rights reserved.
    Keywords: Action recognition | Autism Spectrum Disorder | Patient monitoring | Bag-of-visual-words | Convolutional neural networks


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 11
    حجم فایل: 1862 کیلوبایت

    قیمت: رایگان


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