کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7226328 | 1470612 | 2018 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Wildland Forest Fire Smoke Detection Based on Faster R-CNN using Synthetic Smoke Images
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی (عمومی)
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چکیده انگلیسی
In this paper, Faster R-CNN was used to detect wildland forest fire smoke to avoid the complex manually feature extraction process in traditional video smoke detection methods. Synthetic smoke images are produced by inserting real smoke or simulative smoke into forest background to solve the lack of training data. The models trained by the two kinds of synthetic images respectively are tested in dataset consisting of real fire smoke images. The results show that simulative smoke is the better choice and the model is insensitive to thin smoke. It may be possible to further boost the performance by improving the synthetic process of forest fire smoke images or extending this solution to video sequences.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Engineering - Volume 211, 2018, Pages 441-446
Journal: Procedia Engineering - Volume 211, 2018, Pages 441-446
نویسندگان
Qi-xing Zhang, Gao-hua Lin, Yong-ming Zhang, Gao Xu, Jin-jun Wang,