{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:57:30Z","timestamp":1760245050213},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2018,11,19]],"date-time":"2018-11-19T00:00:00Z","timestamp":1542585600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s13042-018-0891-9","type":"journal-article","created":{"date-parts":[[2018,11,19]],"date-time":"2018-11-19T02:53:27Z","timestamp":1542596007000},"page":"2563-2572","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Depth estimation from infrared video using local-feature-flow neural network"],"prefix":"10.1007","volume":"10","author":[{"given":"Shouchuan","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haitao","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaoyuan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,19]]},"reference":[{"key":"891_CR1","first-page":"1","volume":"3","author":"M Al-Smadi","year":"2018","unstructured":"Al-Smadi M, Talafha B, Al-Ayyoub M et al (2018) Using long short-term memory deep neural networks for aspect-based sentiment analysis of Arabic reviews. Int J Mach Learn Cybern 2018(3):1\u201313","journal-title":"Int J Mach Learn Cybern"},{"key":"891_CR2","doi-asserted-by":"crossref","unstructured":"Andreas J, Rohrbach M, Trevor D, Klein D (2016) Neural module networks. In: IEEE conference on computer vision and pattern recognition, pp 39\u201348","DOI":"10.1109\/CVPR.2016.12"},{"key":"891_CR3","doi-asserted-by":"crossref","unstructured":"Hendricks LA, Venugopalan S, Rohrbach M, Mooney R, Saenko K, Darrell T (2016) Deep compositional captioning: Describing novel object categories without paired training data. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1\u201310","DOI":"10.1109\/CVPR.2016.8"},{"key":"891_CR4","unstructured":"Bi T, Liu Y, Weng D, Wang Y (2016) Monocular depth estimation of outdoor scenes using rgb-d datasets. In: Asian conference on computer vision, pp 88\u201399"},{"key":"891_CR5","doi-asserted-by":"crossref","unstructured":"Cho K, Van Merri\u00ebnboer B, Gulcehre C, Bahdanau D, Bougares F, Schwenk H, Bengio Y (2014) Learning phrase representations using rnn encoder-decoder for statistical machine translation. \n                    arXiv:1406.1078","DOI":"10.3115\/v1\/D14-1179"},{"key":"891_CR6","first-page":"2067","volume":"2015","author":"J Chung","year":"2015","unstructured":"Chung J, Gulcehre C, Cho K et al (2015) Gated feedback recurrent neural networks. Int Conf Mach Learn 2015:2067\u20132075","journal-title":"Int Conf Mach Learn"},{"key":"891_CR7","first-page":"2625","volume":"2015","author":"J Donahue","year":"2015","unstructured":"Donahue J, Hendricks L A, Guadarrama S et al (2015) Long-term recurrent convolutional networks for visual recognition and description. IEEE Conf Comput Vision Pattern Recogn 2015:2625\u20132634","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR8","first-page":"2366","volume":"2014","author":"D Eigen","year":"2014","unstructured":"Eigen D, Puhrsch C, Fergus R et al (2014) Depth map prediction from a single image using a multi-scale deep network. Neural Inf Proc Syst 2014:2366\u20132374","journal-title":"Neural Inf Proc Syst"},{"key":"891_CR9","first-page":"55","volume":"2014","author":"K Fragkiadaki","year":"2014","unstructured":"Fragkiadaki K, Salas M, Arbelaez P et al (2014) Grouping-based low-rank trajectory completion and 3D reconstruction. Neural Inf Proc Syst 2014:55\u201363","journal-title":"Neural Inf Proc Syst"},{"key":"891_CR10","first-page":"1272","volume":"2013","author":"R Garg","year":"2013","unstructured":"Garg R, Roussos A, Agapito L et al (2013) Dense variational reconstruction of non-rigid surfaces from monocular video. IEEE Conf Comput Vision Pattern Recogn 2013:1272\u20131279","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR11","first-page":"580","volume":"2014","author":"R Girshick","year":"2014","unstructured":"Girshick R, Donahue J, Darrell T et al (2014) Rich feature hierarchies for accurate object detection and semantic segmentation. IEEE Conf Comput Vision Pattern Recogn 2014:580\u2013587","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR12","first-page":"5413","volume":"2016","author":"H Ha","year":"2016","unstructured":"Ha H, Im S, Park J et al (2016) High-quality depth from uncalibrated small motion clip. IEEE Conf Comput Vision Pattern Recogn 2016:5413\u20135421","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR13","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"issue":"8","key":"891_CR14","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"Sepp Hochreiter","year":"1997","unstructured":"Hochreiter Sepp, Schmidhuber Jurgen (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"issue":"4","key":"891_CR15","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1109\/TPAMI.2016.2598339","volume":"39","author":"A Karpathy","year":"2017","unstructured":"Karpathy A, Feifei L (2017) Deep visual-semantic alignments for generating image descriptions. IEEE Trans Pattern Anal Mach Intell 39(4):664\u2013676","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"891_CR16","doi-asserted-by":"publisher","first-page":"2144","DOI":"10.1109\/TPAMI.2014.2316835","volume":"36","author":"Kevin Karsch","year":"2014","unstructured":"Karsch Kevin, Liu Ce, Kang Sing Bing (2014) Depth transfer: depth extraction from video using non-parametric sampling. IEEE Trans Pattern Anal Mach Intell 36(11):2144\u20132158","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"891_CR17","first-page":"3514","volume":"2015","author":"N Kong","year":"2015","unstructured":"Kong N, Black MJ (2015) Intrinsic depth: improving depth transfer with intrinsic images. IEEE Conf Comput Vision Pattern Recogn 2015:3514\u20133522","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"issue":"9","key":"891_CR18","doi-asserted-by":"publisher","first-page":"3485","DOI":"10.1109\/TIP.2013.2270375","volume":"22","author":"Janusz Konrad","year":"2013","unstructured":"Konrad Janusz, Wang Meng, Ishwar Prakash, Chen Wu, Mukherjee D (2013) Learning-based, automatic 2d-to-3d image and video conversion. IEEE Trans Image Process 22(9):3485\u20133496","journal-title":"IEEE Trans Image Process"},{"key":"891_CR19","first-page":"1097","volume":"2012","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton GE et al (2012) Imagenet classification with deep convolutional neural networks. Neural Inf Proc Syst 2012:1097\u20131105","journal-title":"Neural Inf Proc Syst"},{"key":"891_CR20","doi-asserted-by":"crossref","unstructured":"Liu B, Gould S, Koller D (2010) Single image depth estimation from predicted semantic labels. Comput Vis Pattern Recognit (CVPR), 2010 IEEE conference on. IEEE, pp 1253\u20131260","DOI":"10.1109\/CVPR.2010.5539823"},{"key":"891_CR21","first-page":"5162","volume":"2015","author":"F Liu","year":"2015","unstructured":"Liu F, Shen C, Lin G et al (2015) Deep convolutional neural fields for depth estimation from a single image. IEEE Trans Pattern Anal Mach Intell 2015:5162\u20135170","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"891_CR22","first-page":"716","volume":"2014","author":"M Liu","year":"2014","unstructured":"Liu M, Salzmann M, He X et al (2014) Discrete-continuous depth estimation from a single image. IEEE Conf Comput Vision Pattern Recogn 2014:716\u2013723","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR23","first-page":"3431","volume":"2015","author":"J Long","year":"2015","unstructured":"Long J, Shelhamer E, Darrell T et al (2015) Fully convolutional networks for semantic segmentation. IEEE Conf Comput Vision Pattern Recogn 2015:3431\u20133440","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"issue":"6","key":"891_CR24","doi-asserted-by":"publisher","first-page":"1795","DOI":"10.1007\/s13042-016-0559-2","volume":"8","author":"Kurosh Madani","year":"2017","unstructured":"Madani Kurosh, Hassan Dayana, Sabourin Christophe (2017) A dual approach for machine-awareness in indoor environment combining pseudo-3d imaging and soft-computing techniques. Int J Mach Learn Cybern 8(6):1795\u20131814","journal-title":"Int J Mach Learn Cybern"},{"key":"891_CR25","first-page":"1682","volume":"2014","author":"M Malinowski","year":"2014","unstructured":"Malinowski M, Fritz M (2014) A multi-world approach to question answering about real-world scenes based on uncertain input. Neural Inf Proc Syst 2014:1682\u20131690","journal-title":"Neural Inf Proc Syst"},{"key":"891_CR26","first-page":"4058","volume":"2016","author":"R Ranftl","year":"2016","unstructured":"Ranftl R, Vineet V, Chen Q, et al (2016) Dense monocular depth estimation in complex dynamic scenes. IEEE Conf Comput Vision Pattern Recogn 2016:4058\u20134066","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR27","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala S, Girshick R, Farhadi A (2016) You only look once: Unified, real-time object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 779\u2013788","DOI":"10.1109\/CVPR.2016.91"},{"issue":"6","key":"891_CR28","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren S, He K, Girshick R B et al (2017) Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"891_CR29","first-page":"5506","volume":"2016","author":"A Roy","year":"2016","unstructured":"Roy A, Todorovic S (2016) Monocular depth estimation using neural regression forest. IEEE Conf Comput Vision Pattern Recogn 2016:5506\u20135514","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR30","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. \n                    arXiv:1409.1556"},{"key":"891_CR31","first-page":"1747","volume":"2016","author":"AV Oord Den","year":"2016","unstructured":"Den Oord A V, Kalchbrenner N, Kavukcuoglu K et al (2016) Pixel recurrent neural networks. Int Conf Mach Learn 2016:1747\u20131756","journal-title":"Int Conf Mach Learn"},{"key":"891_CR32","first-page":"3156","volume":"2015","author":"O Vinyals","year":"2015","unstructured":"Vinyals O, Toshev A, Bengio S et al (2015) Show and tell: a neural image caption generator. IEEE Conf Comput Vision Pattern Recogn 2015:3156\u20133164","journal-title":"IEEE Conf Comput Vision Pattern Recogn"},{"key":"891_CR33","unstructured":"Visin F, Kastner K, Cho K et al (2015) Renet: a recurrent neural network based alternative to convolutional networks. \n                    arXiv:1505.00393"},{"issue":"5","key":"891_CR34","doi-asserted-by":"publisher","first-page":"1447","DOI":"10.1007\/s13042-016-0515-1","volume":"8","author":"Yu Xiao","year":"2017","unstructured":"Xiao Yu, Hua Yu, Tian Xian-Yun, Guang Yu, Li Xiao-mei, Zhang Xue, Wang Ju-Yun (2017) Recognition of college students from weibo with deep neural networks. Int J Mach Learn Cybern 8(5):1447\u20131455","journal-title":"Int J Mach Learn Cybern"},{"issue":"3","key":"891_CR35","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/TPAMI.2010.115","volume":"33","author":"Guofeng Zhang","year":"2011","unstructured":"Zhang Guofeng, Jia Jiaya, Hua Wei, Bao Hujun (2011) Robust bilayer segmentation and motion\/depth estimation with a handheld camera. IEEE Trans Pattern Anal Mach Intell 33(3):603\u2013617","journal-title":"IEEE Trans Pattern Anal Mach Intell"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0891-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-018-0891-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0891-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,12,18]],"date-time":"2019-12-18T11:12:07Z","timestamp":1576667527000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-018-0891-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,19]]},"references-count":35,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["891"],"URL":"https:\/\/doi.org\/10.1007\/s13042-018-0891-9","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11,19]]},"assertion":[{"value":"19 March 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}