![](/images/graphics-bg.png)
Heterogeneous Gray-Temperature Fusion-Based Deep Learning Architecture for Far Infrared Small Target Detection
المؤلفون المشاركون
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-08-22
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
This paper proposes the end-to-end detection of a deep network for far infrared small target detection.
The problem of detecting small targets has been a subject of research for decades and has been applied mainly in the field of surveillance.
Traditional methods focus on filter design for each environment, and several steps are needed to obtain the final detection result.
Most of them work well in a given environment but are vulnerable to severe clutter or environmental changes.
This paper proposes a novel deep learning-based far infrared small target detection method and a heterogeneous data fusion method to solve the lack of semantic information due to the small target size.
Heterogeneous data consists of radiometric temperature data (14-bit) and gray scale data (8-bit), which includes the physical meaning of the target, and compares the effects of the normalization method to fuse heterogeneous data.
Experiments were conducted using an infrared small target dataset built directly on the cloud backgrounds.
The experimental results showed that there is a significant difference in performance according to the various fusion methods and normalization methods, and the proposed detector showed approximately 20% improvement in average precision (AP) compared to the baseline constant false alarm rate (CFAR) detector.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ryu, Junhwan& Kim, Sungho. 2019. Heterogeneous Gray-Temperature Fusion-Based Deep Learning Architecture for Far Infrared Small Target Detection. Journal of Sensors،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1187670
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ryu, Junhwan& Kim, Sungho. Heterogeneous Gray-Temperature Fusion-Based Deep Learning Architecture for Far Infrared Small Target Detection. Journal of Sensors No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1187670
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ryu, Junhwan& Kim, Sungho. Heterogeneous Gray-Temperature Fusion-Based Deep Learning Architecture for Far Infrared Small Target Detection. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1187670
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1187670
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
![](/images/kashef-image.png)