Convolutional Neural Network Based Handgun Detection
Yazarlar (2)
Sabri Kocer
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Web of Science Kapsamındaki Kongre/Sempozyum | ||
| Kongre Adı | 2017 International Conference on Computer Science and Engineering (UBMK) | ||
| Kongre Tarihi | / | ||
| Basıldığı Ülke | Basıldığı Şehir | ||
| Bildiri Linki | https://ieeexplore.ieee.org/abstract/document/8093564/ | ||
| UAK Araştırma Alanları |
Mühendislik
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| Özet |
| Convolutional neural network based methods have provided great success in image classification and object detection tasks. However object detection, unlike the image classification task, requires much more computational intensities and energy consumption. As a result, object detection methods are difficult to integrate into embedded systems with limited resources. In this article, we propose a real-time handgun detection application on the embedded system. This application was implemented with 2 different convolutional neural network based object detection algorithms, and accuracy and speed performances were compared. |
| Anahtar Kelimeler |
| cnn | deep learning | deep neural network | gpu | handgun detection | object detection |
