交通AI算法

应对各类智能化交通业务分析需求，使用深度学习技术进行应用算法的开发，构建交通AI分析算法库。提供面向城市交通运输、公交、出租、交管、海洋交通领域细分业务的22类分析算法模型，包括：人群密度检测、区域入侵检测、场站人流拥堵预警、公交拥挤度检测、营运车辆状态识别、出租车人数检测、安全帽检测、路面抛洒物检测、病害检测、车辆流量统计及跟踪、电动车进电梯检测、道路拥堵预警、船舶在离港数量统计及轨迹跟踪等。

To address the analysis requirements of various intelligent transportation services, develop application algorithms using deep learning technologies, and build a transportation AI analysis algorithm library. It offers 22 categories of analytical algorithm models tailored for segmented business scenarios in urban transportation, public transit, taxi services, traffic management, and maritime transportation, including: crowd density detection, restricted area intrusion detection, passenger flow congestion warning at transit stations, bus crowding detection, operating vehicle status recognition, taxi passenger count detection, hard hat detection, road surface debris detection, pavement disease detection, vehicle flow counting and tracking, electric vehicle entering elevator detection, road congestion warning, and statistics of the number of ships berthing and departing as well as their trajectory tracking.

搜集汇总

背景与挑战

背景概述

该数据集是一个交通领域的AI算法库，包含22类针对不同交通场景的深度学习模型，如人群密度检测和道路拥堵预警，每日更新，数据量达5TB。