دوره 15، شماره 2 - ( 6-1397 )                   جلد 15 شماره 2 صفحات 55-68 | برگشت به فهرست نسخه ها


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ghanbari sorkhi A, Fateh M, Hassanpour H. Intelligent Identifications and Filtering of Unconventional Images Based on Deep Neural Networks. JSDP. 2018; 15 (2) :55-68
URL: http://jsdp.rcisp.ac.ir/article-1-590-fa.html
قنبری سرخی علی، فاتح منصور، حسن‌پور حمید. تشخیص و فیلترینگ هوشمند تصاویر نامتعارف به‌کمک شبکه‌های عصبی عمیق. پردازش علائم و داده‌ها. 1397; 15 (2) :55-68

URL: http://jsdp.rcisp.ac.ir/article-1-590-fa.html


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با پیشرفت روزافزون اینترنت و رسانه‌­های تحت وب، توزیع و اشتراک منابع اطلاعاتی نظیر تصویر در حال افزایش است. اشتراک این منابع علاوه بر مزایای بسیار، خطرات و مشکلاتی نظیر دسترسی به تصاویر نامتعارف دارد که به نوبه خود تهدیدی برای فرهنگ­ جوامع مختلف، به‌­خصوص نوجوانان و جوانان است. امروزه بسیاری از افراد، عضو سایت‌­های اجتماعی از جمله اینستاگرام و فیسبوک هستند. به‌دلیل عدم وجود فیلترینگ هوشمند مناسب، حتی وجود درصدی اندک از تصاویر نامتعارف، فیلتر‌شدن کلیِ سایت‌­های اجتماعی را به همراه دارد که برای کاربران، احساس نارضایتی را به ارمغان می‌آورد. به همین منظور، در این مقاله به تحلیل و بررسی روشی برای دسته­‌بندی تصاویر نامتعارف و فیلترینگ هوشمند آن‌ها پرداخته شده است. یکی از مشکلات این نوع از سامانه‌ها، حجم بالای داده‌های موجود در شبکه­‌های تحت وب و استخراج ویژگی‌­های معنادار در این حجم از داده‌­ها است. در این راستا، در این مقاله روشی جدید، بر پایه شبکه‌­های عصبی عمیق به منظور تشخیص هوشمند تصاویر نامتعارف ارائه شده است. این نوع از شبکه‌ها­، مفاهیم سطح بالا را از روی‌ ویژگی‌های سطح پایین استخراج می­‌کنند و با این استخراج مفاهیم، به دقت مناسبی در دسته‌بندی اطلاعات دست‌ می‎یابند. در این پژوهش، معماری جدیدی برای شناسایی تصاویر نامتعارف پیشنهاد شده است. نتایج به‌دست‌آمده بر روی مجموعه داده به‌نسبت بزرگ آزمایش شده است. این آزمایش‌ها نشان میدهد که روش پیشنهادی دو درصد دقت بیشتری نسبت به روش‌­های جدید مطرح‌شده در شناسایی تصاویر نامتعارف دارد.
 

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نوع مطالعه: پژوهشي | موضوع مقاله: مقالات پردازش تصویر
دریافت: ۱۳۹۵/۷/۱۷ | پذیرش: ۱۳۹۵/۱۲/۱۵ | انتشار: ۱۳۹۷/۶/۲۵ | انتشار الکترونیک: ۱۳۹۷/۶/۲۵

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