基于深度学习的目标检测框架组件研究

深度学习与计算机视觉的结合给目标检测研究领域带来了全新的检测模式，通过对基于深度学习的目标检测网络分析研究，目标检测网络框架可模块化地拆分为特征提取网络、多尺度融合和预测网络三个部分。从组成目标检测网络模块化的角度对各个模块进行了详细的分析综述，并给出了如何根据实际需求来构建适合的模型框架建议，为基于深度学习的目标检测方法研究提供参考。

Research components of object detection framework based on deep learning

The combination of deep learning and computer vision has brought a new detection mode in the field of object detection. Through the analysis of deep learning-based object detection network, the object detection network framework can be modularized and divided into three parts: feature extraction network, multi-scale fusion network and prediction network. This paper analyzes and summarizes each module from the modularized perspective of detection network, and gives suggestions on how to build a suitable model framework according to actual demand, which provides a reference for the research of target detection method based on deep learning.