A lot of research is focused on object detection and it has achieved significant advances with deep learning techniques in recent years. In terms of security, particular interest lies in the automatic detection and classification of weapons within X-ray security imagery in the airport, and drone based platform, with camera have been fast deployed for surveillance purpose. However, these algorithms are not usually optimal for dealing with images captured by drone-based platforms and X-ray imagery, due to various challenges such as limited availability of such images, rapid view point change, different scales and density of object distribution and occlusion an so on. In this presentation, we present initial visualisation results for detection of objects from drone and X-ray space with Faster R-CNN model as baseline architecture. We hope that this preliminary results can boost the research and development in visual analysis of X-ray and drone platforms.