کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4943702 1437640 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fine-tuning deep convolutional neural networks for distinguishing illustrations from photographs
ترجمه فارسی عنوان
تنظیم دقیق شبکه های عصبی کانولوشن عمیق برای تشخیص تصاویر از عکس ها
کلمات کلیدی
سیستم های انباشتگی، فراگیری ماشین، یادگیری عمیق، تصاویر
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Systems for aggregating illustrations require a function for automatically distinguishing illustrations from photographs as they crawl the network to collect images. A previous attempt to implement this functionality by designing basic features that were deemed useful for classification achieved an accuracy of only about 58%. On the other hand, deep neural networks had been successful in computer vision tasks, and convolutional neural networks (CNNs) had performed good at extracting such useful image features automatically. We evaluated alternative methods to implement this classification functionality with focus on deep neural networks. As the result of experiments, the method that fine-tuned deep convolutional neural network (DCNN) acquired 96.8% accuracy, outperforming the other models including the custom CNN models that were trained from scratch. We conclude that DCNN with fine-tuning is the best method for implementing a function for automatically distinguishing illustrations from photographs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 66, 30 December 2016, Pages 295-301
نویسندگان
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