کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4942569 1437411 2018 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Using machine learning to detect and localize concealed objects in passive millimeter-wave images
ترجمه فارسی عنوان
با استفاده از یادگیری ماشین برای تشخیص و محاسبه اشیاء پنهان در تصاویر موج های غیرفعال
کلمات کلیدی
تشخیص تهدید، فراگیری ماشین، تصویربرداری از یک میلیمتری منفعل،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


- A new approach to the detection of hidden objects in PMMWI based on machine learning.
- A comparative experimental study between two type of features and six classifiers.
- A new database of Passive Millimeter Wave Images (PMMWI).

The detection and location of objects concealed under clothing is a very challenging task that has crucial applications in security. In this domain, passive millimeter-wave images (PMMWIs) can be used. However, the quality of the acquired images, and the unknown position, shape, and size of hidden objects render this task difficult. In this paper, we propose a machine learning-based solution to this detection/localization problem. Our method outperforms currently used approaches. The effect of non-stationary noise on different classification algorithms is analyzed and discussed, and a detailed experimental comparative study of classification techniques is presented using a new and comprehensive PMMWI database. The low computational testing cost of this solution allows for its use in real-time applications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 67, January 2018, Pages 81-90
نویسندگان
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