استادیار، گروه مهندسی کامپیوتر و فناوری اطلاعات، دانشکده فنی مهندسی، دانشگاه شاهد، تهران، ایران
چکیده
روشهای متداول موقعیتیابی متن در تصاویر طبیعی دارای چالش فضای زیاد جستجو جهت تشخیص دقیق، صحیح، سریع و کارا است و برای پشتیبانی از دادههای عظیم تصویری به یک مسئله سخت لاینحل تبدیل میشود. میتوان کاهش محاسبات پیچیده را با هدف کنترل فضای جستجو، منابع مصرفی و هزینهها، با برخورداری از تکنیکهای نرمافزاری در فضای سختافزاری چندهستهای، ساختارهای گرید و رایانش ابری شکل داد. موقعیتیابی و خواندن نوری متون در سطوح مختلف پاراگراف، خط متن، کلمه و کاراکتر در دادههای عظیم بهطور وحشتناکی به پیچیدگی آن میافزاید. در این مقاله روشهای عمومی غیریادگیر موقعیتیابی متون در تصاویر کمحجم و روشهای متداول دادههای حجیم طبیعی بررسی شده و مدلی مناسب دارای تحلیلگر استراتژیک تصویر با استفاده از عاملهای هوشمند و باتهای زیرک برای پردازش دادههای عظیم تصویری جهت موقعیتیابی متون توسط روباتها ارائه و در کنار مجموعه دادههای متفاوت و معیارهای ارزیابی مختلف تشریح شده است.
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