کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4943212 | 1437617 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Staff-line removal with selectional auto-encoders
ترجمه فارسی عنوان
حذف ستون خط با انتخاب خودکار رمزگذار
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کلمات کلیدی
حذف کارکنان خط، تشخیص موسیقی نوری، خودکار رمزگذاران، شبکه های متخلخل
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Staff-line removal is an important preprocessing stage as regards most Optical Music Recognition systems. The common procedures employed to carry out this task involve image processing techniques. In contrast to these traditional methods, which are based on hand-engineered transformations, the problem can also be approached from a machine learning point of view if representative examples of the task are provided. We propose doing this through the use of a new approach involving auto-encoders, which select the appropriate features of an input feature set (Selectional Auto-Encoders). Within the context of the problem at hand, the model is trained to select those pixels of a given image that belong to a musical symbol, thus removing the lines of the staves. Our results show that the proposed technique is quite competitive and significantly outperforms the other state-of-art strategies considered, particularly when dealing with grayscale input images.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 89, 15 December 2017, Pages 138-148
Journal: Expert Systems with Applications - Volume 89, 15 December 2017, Pages 138-148
نویسندگان
Antonio-Javier Gallego, Jorge Calvo-Zaragoza,