水准点(测量)
计算机科学
人工智能
目标检测
深度学习
任务(项目管理)
对象(语法)
GSM演进的增强数据速率
机器学习
视觉对象识别的认知神经科学
模式识别(心理学)
计算机视觉
作者
Syed Sahil Abbas Zaidi,Mohammad Samar Ansari,Asra Aslam,Nadia Kanwal,Mamoona Naveed Asghar,Brian Lee
标识
DOI:10.1016/j.dsp.2022.103514
摘要
Object Detection is the task of classification and localization of objects in an image or video. It has gained prominence in recent years due to its widespread applications. This article surveys recent developments in deep learning based object detectors. Concise overview of benchmark datasets and evaluation metrics used in detection is also provided along with some of the prominent backbone architectures used in recognition tasks. It also covers contemporary lightweight classification models used on edge devices. Lastly, we compare the performances of these architectures on multiple metrics.
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