کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
9952354 1448264 2018 21 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An automatic methodology for analyzing sorting level of rock particles
ترجمه فارسی عنوان
یک روش خودکار برای تجزیه و تحلیل سطح مرتب سازی ذرات سنگ
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Previous efforts on analyzing the sorting level of rock particles rely on particle segmentation, which is time-consuming and inaccurate due to lighting and intra-particle statistical variations. With high-level features learned from a deep neural network, we directly conduct the classification of sorting in rocks. Our approach avoids the need for laborious segmentation and is entirely automatic. We use an off-the-shelf convolutional neural network (CNN) model that has been pre-trained on a large scale image dataset to extract feature representations for our rock images. Then we trained a support vector machine (SVM) classifier with the feature representations as input. The experiments show that the off-the-shelf CNN features lead to significantly improved results for the classification compared with handcrafted features and low-level K-means features.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Geosciences - Volume 120, November 2018, Pages 97-104
نویسندگان
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