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Secondly, in order to improve the rate of subsequent similar frame detection, the color as well as texture features of the road are extracted from the detection results of the first frame, and the corresponding Gaussian mixture models (GMMs) are constructed based on Orchard-Bouman, and then the Gibbs energy function is used to achieve road detection in subsequent frames. Finally, the above algorithm is verified in a real unstructured road scene, and the experimental results show that the algorithm is 98.4% accurate and can process 58 frames per second with 1024\u00d7960 pixels.<\/jats:p>","DOI":"10.3233\/jifs-211733","type":"journal-article","created":{"date-parts":[[2021,12,7]],"date-time":"2021-12-07T14:11:20Z","timestamp":1638886280000},"page":"2471-2489","source":"Crossref","is-referenced-by-count":2,"title":["Real-time unstructured road detection based on CNN and Gibbs energy function"],"prefix":"10.1177","volume":"42","author":[{"given":"Mingzhou","family":"Liu","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiannan","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Hefei University of Technology, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-211733_ref1","unstructured":"Research Institute of Highway Ministry of Transport, The Blue Book of Road Safety in China 2014 [M], Beijing: China Communications Press; 2015, p. 13\u201314."},{"issue":"99","key":"10.3233\/JIFS-211733_ref2","first-page":"1","article-title":"Motor Anomaly Detection for Unmanned Aerial Vehicles Using Reinforcement Learning[J]","volume":"PP","author":"Lu","year":"2017","journal-title":"IEEE Internet of Things Journal"},{"issue":"1","key":"10.3233\/JIFS-211733_ref4","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MIM.2006.1634964","article-title":"Intelligent Vehicle Technology and Trends \u2013 [Book review] [J]","volume":"9","author":"Ziomek","year":"2006","journal-title":"Instrumentation & Measurement Magazine IEEE"},{"issue":"2","key":"10.3233\/JIFS-211733_ref5","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MITS.2010.938166","article-title":"Emergency Services in Future Intelligent Transportation Systems Based on Vehicular Communication Networks[J]","volume":"2","author":"Martinez","year":"2010","journal-title":"IEEE Intelligent Transportation Systems Magazine"},{"key":"10.3233\/JIFS-211733_ref6","doi-asserted-by":"crossref","unstructured":"Francisco Javier Ariza-L\u00f3pez and Jos\u00e9 Luis Garc\u00eda Balboa, Generalization-oriented road line segmentation by means of an artificial neural network applied over a moving window[J], Pattern Recognition 41(5) (2008), 1593\u20131609.","DOI":"10.1016\/j.patcog.2007.11.009"},{"key":"10.3233\/JIFS-211733_ref7","doi-asserted-by":"crossref","unstructured":"Ardiyanto I. and Adji T.B. , Deep residual coalesced convolutional network for efficient semantic road segmentation[J], IPSJ Transactions on Computer Vision & Applications 9(1) (2017).","DOI":"10.1186\/s41074-017-0020-9"},{"issue":"11","key":"10.3233\/JIFS-211733_ref8","first-page":"521","article-title":"Road Sign Detection with Weather\/Illumination Classifications and Adaptive Color Models in Various Road Images[J]","volume":"4","author":"Kim","year":"2015","journal-title":"Anesthesiology"},{"key":"10.3233\/JIFS-211733_ref9","doi-asserted-by":"crossref","unstructured":"Yao J. , Ramalingam S. , Taguchi Y. , et al., Estimating drivable collision-free space from monocular video[C], Applications of Computer Vision, 2015.","DOI":"10.1109\/WACV.2015.62"},{"issue":"8","key":"10.3233\/JIFS-211733_ref10","doi-asserted-by":"crossref","first-page":"143","DOI":"10.3901\/JME.2013.08.143","article-title":"Algorithm for urban road detection based on uncertain Bezier deformable template[J]","volume":"49","author":"Wang","year":"2013","journal-title":"Journal of Mechanical Engineering"},{"key":"10.3233\/JIFS-211733_ref11","doi-asserted-by":"crossref","unstructured":"Cheng G. , Qian Y. and Elder J.H. , Fusing Geometry and Appearance for Road Segmentation[C], IEEE International Conference on Computer Vision Workshop, IEEE, 2018.","DOI":"10.1109\/ICCVW.2017.28"},{"key":"10.3233\/JIFS-211733_ref12","first-page":"1729","author":"Wang","year":"2010","journal-title":"IEEE International Conference on Information and Automation"},{"key":"10.3233\/JIFS-211733_ref13","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1109\/CVPR.2009.5206787","article-title":"Vanishing point detection for road detection","author":"Kong","year":"2009","journal-title":"Computer Vision and Pattern Recognition (CVPR), 2009 IEEE Conference on. 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