{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:27:54Z","timestamp":1750220874060,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,1,7]],"date-time":"2020-01-07T00:00:00Z","timestamp":1578355200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Russian Ministry of Education and Science","award":["RFMEFI60918X0005"],"award-info":[{"award-number":["RFMEFI60918X0005"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,1,7]]},"DOI":"10.1145\/3378184.3378190","type":"proceedings-article","created":{"date-parts":[[2020,2,18]],"date-time":"2020-02-18T03:31:51Z","timestamp":1581996711000},"page":"1-5","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Segmification"],"prefix":"10.1145","author":[{"given":"Vladislav","family":"Ostankovich","sequence":"first","affiliation":[{"name":"Center for Technologies in Robotics and Mechatronics Components, Innopolis University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rauf","family":"Yagfarov","sequence":"additional","affiliation":[{"name":"Center for Technologies in Robotics and Mechatronics Components, Innopolis University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,2,17]]},"reference":[{"volume-title":"Segnet: A deep convolutional encoder-decoder architecture for image segmentation","year":"2017","author":"Badrinarayanan Vijay","key":"e_1_3_2_1_1_1"},{"volume-title":"Linknet: Exploiting encoder representations for efficient semantic segmentation. In 2017 IEEE Visual Communications and Image Processing (VCIP)","year":"2017","author":"Chaurasia Abhishek","key":"e_1_3_2_1_2_1"},{"volume-title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","year":"2017","author":"Chen Liang-Chieh","key":"e_1_3_2_1_3_1"},{"key":"e_1_3_2_1_4_1","unstructured":"Liang-Chieh Chen George Papandreou Florian Schroff and Hartwig Adam. 2017. Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587 (2017).  Liang-Chieh Chen George Papandreou Florian Schroff and Hartwig Adam. 2017. Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587 (2017)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Mark Everingham Luc Van Gool Christopher KI Williams John Winn and Andrew Zisserman. 2010. The pascal visual object classes (voc) challenge. International journal of computer vision 88 2 (2010) 303--338.  Mark Everingham Luc Van Gool Christopher KI Williams John Winn and Andrew Zisserman. 2010. The pascal visual object classes (voc) challenge. International journal of computer vision 88 2 (2010) 303--338.","DOI":"10.1007\/s11263-009-0275-4"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_8_1","unstructured":"Sergey Ioffe and Christian Szegedy. 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 (2015).  Sergey Ioffe and Christian Szegedy. 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 (2015)."},{"volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","year":"2014","author":"Kingma Diederik P","key":"e_1_3_2_1_9_1"},{"key":"e_1_3_2_1_10_1","unstructured":"Alex Krizhevsky Geoffrey Hinton etal 2009. Learning multiple layers of features from tiny images. Technical Report. Citeseer.  Alex Krizhevsky Geoffrey Hinton et al. 2009. Learning multiple layers of features from tiny images. Technical Report. Citeseer."},{"volume-title":"Enet: A deep neural network architecture for real-time semantic segmentation. arXiv preprint arXiv:1606.02147","year":"2016","author":"Paszke Adam","key":"e_1_3_2_1_11_1"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael Bernstein etal 2015. Imagenet large scale visual recognition challenge. International journal of computer vision 115 3 (2015) 211--252.  Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael Bernstein et al. 2015. Imagenet large scale visual recognition challenge. International journal of computer vision 115 3 (2015) 211--252.","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_14_1","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014).  Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"e_1_3_2_1_15_1","unstructured":"Fisher Yu Wenqi Xian Yingying Chen Fangchen Liu Mike Liao Vashisht Madhavan and Trevor Darrell. 2018. Bdd100k: A diverse driving video database with scalable annotation tooling. arXiv preprint arXiv:1805.04687 (2018).  Fisher Yu Wenqi Xian Yingying Chen Fangchen Liu Mike Liao Vashisht Madhavan and Trevor Darrell. 2018. Bdd100k: A diverse driving video database with scalable annotation tooling. arXiv preprint arXiv:1805.04687 (2018)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"}],"event":{"name":"APPIS 2020: 3rd International Conference on Applications of Intelligent Systems","acronym":"APPIS 2020","location":"Las Palmas de Gran Canaria Spain"},"container-title":["Proceedings of the 3rd International Conference on Applications of Intelligent Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3378184.3378190","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3378184.3378190","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:24:01Z","timestamp":1750202641000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3378184.3378190"}},"subtitle":["Solving road segmentation and scene classification tasks for self-driving cars using one neural network"],"short-title":[],"issued":{"date-parts":[[2020,1,7]]},"references-count":16,"alternative-id":["10.1145\/3378184.3378190","10.1145\/3378184"],"URL":"https:\/\/doi.org\/10.1145\/3378184.3378190","relation":{},"subject":[],"published":{"date-parts":[[2020,1,7]]},"assertion":[{"value":"2020-02-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}