...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Neural processing letters >An Evaluation of RetinaNet on Indoor Object Detection for Blind and Visually Impaired Persons Assistance Navigation
【24h】

An Evaluation of RetinaNet on Indoor Object Detection for Blind and Visually Impaired Persons Assistance Navigation

机译：视网膜对盲人和视障人士援助导航的室内物体检测评价

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Indoor object detection presents a computer vision task that deals with the detection of specific indoor classes. This task attracts a lot of attention, especially in the last few years. The strong interest related to this field can be explained by the big importance of this task for indoor assistance navigation for visually impaired people and also by the phenomenal development of the deep convolutional neural networks (Deep CNN). In this paper, an effort is made to perform a new indoor object detector using the deep convolutional neural network-based framework. The framework is built based on the deep convolutional neural network "RetinaNet". Evaluation is done by using various backbones as ResNet, DenseNet, and VGGNet in order to improve detection performances and processing time. We obtained very encouraging results coming up to 84.61% mAP as detection precision.
机译：室内对象检测提供了一种涉及检测特定室内课程的计算机视觉任务。这项任务吸引了很多关注，特别是在过去几年中。对于这项任务对视障人士的室内援助导航以及深度卷积神经网络（深CNN）的现象发展，可以解释与此领域相关的强烈兴趣。在本文中，使用基于深度卷积神经网络的框架来执行新的室内物体检测器。该框架是基于深度卷积神经网络“RetinAnet”的构建。评估是通过使用各种骨干，作为RESET，DENNENET和VGGNET来完成，以改善检测性能和处理时间。我们获得了非常令人鼓舞的结果，达到84.61％的地图作为检测精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号