ID 原文 译文
15355 针对目前无人机航拍影像杆塔识别算法中,普遍是无人机通过倾斜摄影技术获取到杆塔的原始遥观影像数据,经过机器学习训练,识别其余图片数据中的杆塔。 According to the current aerial image tower identification algorithm of UAV, it is common for UAV to obtain the original remote viewing image data of the tower through tilt photography technology, and identify the tower in the rest image data through machine learning training.
15356 其中存在获取机器训练所需的图片数据来源缓慢、只能二维识别图片中杆塔等问题。 Among them, there are some problems such as slow source of image data needed for machine training and two-dimensional identification of the tower in the picture.
15357 提出了基于深度学习的杆塔三维姿态实时估计的算法。 In this paper, an algorithm based on deep-object-pose is proposed for re-al-time aerial aerial aerial aerial recognition of the three-dimensional attitude of the tower.
15358 首先,通过三维平台合成影像数据； Firstly, image data is synthesized by three-dimensional platform.
15359 其次,通过Deep-Object-Pose训练及其处理； Secondly, deep-object-pose training and treatment were carried out.
15360 然后测试真实的图片数据或者实时视频,达到智能识别杆塔的三维空间姿态信息。 Then test the real picture data or re-al-time video, to achieve intelligent recognition of the tower's three-dimensional attitude information.
15361 该算法为无人机自动寻找杆塔目标和智能精细化巡检提供新的思路。 The experimental results show that this algorithm will provide a new idea for uav to automatically find the target of tower and intelligent fine inspection.
15362 SRAM型FPGA的低成本及其现场可编程性使其在航空航天工业中很受欢迎。 SRAM-based FPGAs are popular in the aerospace industry for their field programmability and low cost.
15363 为解决FPGA受宇宙辐射引起的单粒子效应(Single Event Effect,SEE),常使用三模冗余(Triple Modular Redundancy,TMR)这一缓解技术。 However, they suffer from cosmic radiation-induced single event effect( SEE).
15364 该技术通常与配置刷新技术一起用来加固基于SRAM的FPGA。 Triple modular redundancy( TMR) is a well-known technique to mitigate SEEs in FPGAs that is often used with another SEE mitigation technique known as configuration scrubbing.