کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1778803 1523733 2016 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Sunspot drawings handwritten character recognition method based on deep learning
ترجمه فارسی عنوان
روش تشخیص شخصیت دست نوشته نقاشی لکه های خورشیدی مبتنی بر یادگیری عمیق
کلمات کلیدی
نقشه های لکه های خورشیدی؛ شبکه های عصبی کانولوشنی؛ شخصیت دست خط؛ شناخت
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم نجوم و فیزیک نجومی
چکیده انگلیسی


• Convolution neural network (CNN) is applied to recognize handwritten characters in scanned sunspot drawings.
• A recognition model for handwritten characters is obtained by CNN method.
• The daily full-disc sunspot numbers and full-disc sunspot areas can be obtained from the recognized information.

High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: New Astronomy - Volume 45, May 2016, Pages 54–59
نویسندگان
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