{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/road-segmentation-using-cnn-and-distributed","title":"Road Segmentation Using CNN and Distributed LSTM","arxiv_id":"1808.04450","date":"2018-08-10","proceeding":null,"authors":["Yecheng Lyu","Lin Bai","Xinming Huang"],"abstract":"In automated driving systems (ADS) and advanced driver-assistance systems\n(ADAS), an efficient road segmentation is necessary to perceive the drivable\nregion and build an occupancy map for path planning. The existing algorithms\nimplement gigantic convolutional neural networks (CNNs) that are\ncomputationally expensive and time consuming. In this paper, we introduced\ndistributed LSTM, a neural network widely used in audio and video processing,\nto process rows and columns in images and feature maps. We then propose a new\nnetwork combining the convolutional and distributed LSTM layers to solve the\nroad segmentation problem. In the end, the network is trained and tested in\nKITTI road benchmark. The result shows that the combined structure enhances the\nfeature extraction and processing but takes less processing time than pure CNN\nstructure.","url_abs":"http://arxiv.org/abs/1808.04450v2","url_pdf":"http://arxiv.org/pdf/1808.04450v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"road-segmentation-using-cnn-and-distributed","repo_url":"https://github.com/Evvvvvvvva/AutonomousDriving","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"road-segmentation-using-cnn-and-distributed","repo_url":"https://github.com/ShirSherbet/Autonomous-Driving","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"road-segementation","task_name":"Road Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}