用于动态交通对象检测的特征增强型 FCOS 算法

IF 3.2 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Connection Science Pub Date : 2024-03-01 DOI:10.1080/09540091.2024.2321345

Tuqiang Zhou, Wei Liu, Haoran Li

引用次数: 0

摘要

物体检测的发展对实现完全自动驾驶具有重要作用，而特征提取是物体检测的关键步骤。目前，全球范围内已出现了大量的物体检测方法，但仍存在一些问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A feature enhancement FCOS algorithm for dynamic traffic object detection

The development of object detection plays an important role in the realisation of fully autonomous driving, and the feature extraction is the key step for object detection. There has been significa...

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来源期刊

Connection Science 工程技术-计算机：理论方法

CiteScore

6.50

自引率

39.60%

发文量

审稿时长

3 months

期刊介绍： Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing. A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.