Github Nexdata Ai 122 People Passenger Behavior Recognition Data

Github Nexdata Ai 122 People Passenger Behavior Recognition Data Passenger behavior recognition dataset. contribute to nexdata ai 122 people passenger behavior recognition data development by creating an account on github. The 1,444 passenger behavior recognition data covers multiple ages, time periods and light exposure. passenger behavior includes passenger normal behavior, passenger abnormal behavior (passenger motion sickness behavior, passenger sleepiness behavior, passenger lost children & items behaviors).

Nexdata 1000 People Passenger Behavior Recognition Data Datasets At The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior (passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). Passenger behavior recognition dataset. contribute to nexdata ai 122 people passenger behavior recognition data development by creating an account on github. The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior(passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior (passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior).

Nexdata Github The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior(passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior (passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). This dataset is just a sample of 122 people passenger behavior recognition data (paid dataset). the data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). 随着智能交通系统的快速发展，乘客行为识别成为提升出行安全与服务质量的关键研究方向。 nexdata passenger behavior recognition data数据集由nexdata机构构建，专注于通过计算机视觉技术分析车内乘客的多元行为模式。. The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior (passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). 数据集简介 122人乘客行为识别数据涵盖多年龄段、多时间段、多人种（白种人，黑种人和印度人）。 乘客行为包括乘客正常行为，乘客异常行为（乘客晕车行为，乘客困意行为，乘客遗落物品行为）。 在采集设备方面，采用了可见光和红外双目摄像头。.

Nexdata 1000 People Passenger Behavior Recognition Data At Main This dataset is just a sample of 122 people passenger behavior recognition data (paid dataset). the data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). 随着智能交通系统的快速发展，乘客行为识别成为提升出行安全与服务质量的关键研究方向。 nexdata passenger behavior recognition data数据集由nexdata机构构建，专注于通过计算机视觉技术分析车内乘客的多元行为模式。. The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior (passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). 数据集简介 122人乘客行为识别数据涵盖多年龄段、多时间段、多人种（白种人，黑种人和印度人）。 乘客行为包括乘客正常行为，乘客异常行为（乘客晕车行为，乘客困意行为，乘客遗落物品行为）。 在采集设备方面，采用了可见光和红外双目摄像头。.

Nexdata 1000 People Passenger Behavior Recognition Data At Main The data includes multiple age groups, multiple time periods and multiple races (caucasian, black, indian). the passenger behaviors include passenger normal behavior, passenger abnormal behavior (passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). 数据集简介 122人乘客行为识别数据涵盖多年龄段、多时间段、多人种（白种人，黑种人和印度人）。 乘客行为包括乘客正常行为，乘客异常行为（乘客晕车行为，乘客困意行为，乘客遗落物品行为）。 在采集设备方面，采用了可见光和红外双目摄像头。.