مجله ماشین بینایی و پردازش تصویر

مجله ماشین بینایی و پردازش تصویر

یک روش هوشمند جدید مبتنی بر شبکه‏‏ های کپسولی برای طبقه‏ بندی کشتی ‏های دریایی

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشگاه بین المللی امام خمینی، قزوین، ایران
2 دانشکده مهندسی برق و رباتیک، دانشگاه صنعتی شاهرود، سمنان
3 گروه مهندسی برق کنترل، دانشکده فنی و مهندسی، دانشگاه بین المللی امام خمینی (ره) قزوین.
چکیده
شناسایی و طبقه‏ بندی دقیق کشتی‌ها نقش مهمی در پایش هوشمند ترافیک دریایی، امنیت دریایی و مدیریت عملیات امداد و نجات دارد. با این حال، پیچیدگی محیط‌های دریایی، تغییرات جوی، شرایط نوری نامناسب و شباهت ظاهری کشتی‌ها، چالش‌های جدی برای سیستم‌های شناسایی ایجاد می‌کند. در این مقاله، یک روش هوشمند جدید مبتنی بر شبکه‌های کپسولی برای طبقه‌بندی تصاویر کشتی‌های دریایی ارائه شده است. شبکه‌های کپسولی با استفاده از کپسول‌ها به‌عنوان واحدهای پردازش اطلاعات، قادر به حفظ روابط فضایی بین ویژگی‌ها بوده و اطلاعات جامع‌تری از ساختار اشیا ارائه می‌دهند. این ویژگی باعث افزایش صحت تصمیم‌گیری مدل می‌شود. برای ارزیابی عملکرد مدل پیشنهادی، از مجموعه داده MARVEL با 24 هزار تصویر در ۸ دسته استفاده شد. در آزمایش‌های انجام شده، دقت کلی مدل در طبقه‌بندی تصاویر 61/97 درصد بود. در میان دسته ‏ها بیشترین دقت مربوط به دسته کشتی‌های کروز با ۹۹ درصد و کمترین دقت مربوط به دسته ناوهای هواپیمابر با ۹۵ درصد بود. هم‏چنین نتایج نشان داد که مدل پیشنهادی در شرایط نوری متفاوت، فاصله‌های زیاد و وجود چندین شیء در تصویر عملکرد مناسبی دارد. مقایسه دقت، حساسیت و عملکرد زمانی مدل پیشنهادی با شبکه‌های عمیق شناخته‌شده مانند GoogleNet، ResNet و VGGNet نشان داد که مدل پیشنهادی در بسیاری از شرایط برتر عمل می‌کند. این یافته‌ها نشان دادند که مدل ما ضمن عملکرد مناسب، می‏تواند به عنوان ابزاری قدرتمند و مؤثر برای طبقه‌بندی کشتی‌های دریایی در سامانه‌های نظارتی مورد استفاده قرار گیرد.
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