{"title":"基于神经网络的道路分割","authors":"Tsz Hong Lau","doi":"10.61366/2576-2176.1061","DOIUrl":null,"url":null,"abstract":"Autonomous driving is the next biggest technological ad-vance in the automobile industry. However, the current technology is still very much in its infancy. Networks of sensors such as cameras and LIDAR systems are used to record and measure the road condition. While neural networks are used to understand the road condition and make the correct de-cision to drive the vehicle. In this paper, we are specifically focusing on the road segmentation of autonomous vehicle technology. We will be going over the two approaches to road segmentation by Oliveira, et al [5] and Caltagirone, et al [2], and we will compare the performance of each approach on a road benchmark dataset called KITTI dataset.","PeriodicalId":113813,"journal":{"name":"Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Road Segmentation with Neural Networks\",\"authors\":\"Tsz Hong Lau\",\"doi\":\"10.61366/2576-2176.1061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Autonomous driving is the next biggest technological ad-vance in the automobile industry. However, the current technology is still very much in its infancy. Networks of sensors such as cameras and LIDAR systems are used to record and measure the road condition. While neural networks are used to understand the road condition and make the correct de-cision to drive the vehicle. In this paper, we are specifically focusing on the road segmentation of autonomous vehicle technology. We will be going over the two approaches to road segmentation by Oliveira, et al [5] and Caltagirone, et al [2], and we will compare the performance of each approach on a road benchmark dataset called KITTI dataset.\",\"PeriodicalId\":113813,\"journal\":{\"name\":\"Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.61366/2576-2176.1061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.61366/2576-2176.1061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Autonomous driving is the next biggest technological ad-vance in the automobile industry. However, the current technology is still very much in its infancy. Networks of sensors such as cameras and LIDAR systems are used to record and measure the road condition. While neural networks are used to understand the road condition and make the correct de-cision to drive the vehicle. In this paper, we are specifically focusing on the road segmentation of autonomous vehicle technology. We will be going over the two approaches to road segmentation by Oliveira, et al [5] and Caltagirone, et al [2], and we will compare the performance of each approach on a road benchmark dataset called KITTI dataset.