{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:04:32Z","timestamp":1760609072506,"version":"3.41.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319929996"},{"type":"electronic","value":"9783319930008"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-93000-8_47","type":"book-chapter","created":{"date-parts":[[2018,6,5]],"date-time":"2018-06-05T05:50:47Z","timestamp":1528177847000},"page":"419-426","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Real-Time Multispectral Pedestrian Detection with a Single-Pass Deep Neural Network"],"prefix":"10.1007","author":[{"given":"Maarten","family":"Vandersteegen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kristof","family":"Van Beeck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Toon","family":"Goedem\u00e9","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,6,6]]},"reference":[{"key":"47_CR1","doi-asserted-by":"crossref","unstructured":"Zhang, S., Benenson, R., Omran, M., Hosang, J., Schiele, B.: How far are we from solving pedestrian detection? In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1259\u20131267 (2016)","DOI":"10.1109\/CVPR.2016.141"},{"key":"47_CR2","doi-asserted-by":"crossref","unstructured":"Hwang, S., Park, J., Kim, N., Choi, Y., So Kweon, I.: Multispectral pedestrian detection: benchmark dataset and baseline. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1037\u20131045 (2015)","DOI":"10.1109\/CVPR.2015.7298706"},{"key":"47_CR3","doi-asserted-by":"crossref","unstructured":"De Smedt, F., Puttemans, S., Goedem\u00e9, T.: How to reach top accuracy for a visual pedestrian warning system from a car? In: 2016 6th IEEE International Conference on Image Processing Theory Tools and Applications (IPTA), pp. 1\u20136 (2016)","DOI":"10.1109\/IPTA.2016.7820997"},{"key":"47_CR4","doi-asserted-by":"crossref","unstructured":"Redmon, J., Farhadi, A.: Yolo9000: better, faster, stronger. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6517\u20136525 (2017)","DOI":"10.1109\/CVPR.2017.690"},{"key":"47_CR5","doi-asserted-by":"crossref","unstructured":"Tijtgat, N., Van Ranst, W., Volckaert, B., Goedem\u00e9, T., De Turck, F.: Embedded real-time object detection for a UAV warning system. In: The International Conference on Computer Vision, ICCV 2017, pp. 2110\u20132118 (2017)","DOI":"10.1109\/ICCVW.2017.247"},{"key":"47_CR6","doi-asserted-by":"crossref","unstructured":"K\u00f6nig, D., Adam, M., Jarvers, C., Layher, G., Neumann, H., Teutsch, M.: Fully convolutional region proposal networks for multispectral person detection. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 243\u2013250. IEEE (2017)","DOI":"10.1109\/CVPRW.2017.36"},{"key":"47_CR7","doi-asserted-by":"crossref","unstructured":"Liu, J., Zhang, S., Wang, S., Metaxas, D.: Multispectral deep neural networks for pedestrian detection. In: Proceedings of BMVC, pp. 73.1\u201373.13, September 2016","DOI":"10.5244\/C.30.73"},{"key":"47_CR8","unstructured":"Wagner, J., Fischer, V., Herman, M., Behnke, S.: Multispectral pedestrian detection using deep fusion convolutional neural networks. In: 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pp. 509\u2013514 (2016)"},{"key":"47_CR9","doi-asserted-by":"crossref","unstructured":"Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 886\u2013893. IEEE (2005)","DOI":"10.1109\/CVPR.2005.177"},{"key":"47_CR10","doi-asserted-by":"crossref","unstructured":"Doll\u00e1r, P., Tu, Z., Perona, P., Belongie, S.: Integral channel features (2009)","DOI":"10.5244\/C.23.91"},{"issue":"8","key":"47_CR11","doi-asserted-by":"publisher","first-page":"1532","DOI":"10.1109\/TPAMI.2014.2300479","volume":"36","author":"P Doll\u00e1r","year":"2014","unstructured":"Doll\u00e1r, P., Appel, R., Belongie, S., Perona, P.: Fast feature pyramids for object detection. IEEE Trans. Pattern Anal. Mach. Intell. 36(8), 1532\u20131545 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"47_CR12","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: Towards real-time object detection with region proposal networks. In: Advances in neural information processing systems, pp. 91\u201399 (2015)"},{"key":"47_CR13","doi-asserted-by":"crossref","unstructured":"Choi, H., Kim, S., Park, K., Sohn, K.: Multi-spectral pedestrian detection based on accumulated object proposal with fully convolutional networks. In: 2016 23rd International Conference on Pattern Recognition (ICPR), pp. 621\u2013626. IEEE (2016)","DOI":"10.1109\/ICPR.2016.7899703"},{"key":"47_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/978-3-319-46448-0_2","volume-title":"Computer Vision \u2013 ECCV 2016","author":"W Liu","year":"2016","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., Berg, A.C.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21\u201337. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2"},{"issue":"6","key":"47_CR15","doi-asserted-by":"publisher","first-page":"820","DOI":"10.3390\/s16060820","volume":"16","author":"A Gonz\u00e1lez","year":"2016","unstructured":"Gonz\u00e1lez, A., Fang, Z., Socarras, Y., Serrat, J., V\u00e1zquez, D., Xu, J., L\u00f3pez, A.M.: Pedestrian detection at day\/night time with visible and FIR cameras: a comparison. Sensors 16(6), 820 (2016)","journal-title":"Sensors"},{"key":"47_CR16","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp. 1097\u20131105 (2012)"},{"issue":"2","key":"47_CR17","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"Everingham, M., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: The pascal visual object classes (VOC) challenge. Int. J. Comput. Vis. 88(2), 303\u2013338 (2010)","journal-title":"Int. J. Comput. Vis."},{"key":"47_CR18","doi-asserted-by":"crossref","unstructured":"Hosang, J., Omran, M., Benenson, R., Schiele, B.: Taking a deeper look at pedestrians. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4073\u20134082 (2015)","DOI":"10.1109\/CVPR.2015.7299034"},{"key":"47_CR19","doi-asserted-by":"crossref","unstructured":"Puttemans, S., Callemein, T., Goedem\u00e9, T.: Building robust industrial applicable object detection models using transfer learning and single pass deep learning architectures. In: Proceedings of the International Conference on Computer Vision Theory and Applications (2018, to appear)","DOI":"10.5220\/0006562002090217"},{"issue":"4","key":"47_CR20","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1109\/TPAMI.2011.155","volume":"34","author":"P Dollar","year":"2012","unstructured":"Dollar, P., Wojek, C., Schiele, B., Perona, P.: Pedestrian detection: An evaluation of the state of the art. IEEE Trans. Pattern Anal. Mach. Intell. 34(4), 743\u2013761 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Recognition"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-93000-8_47","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T23:51:58Z","timestamp":1751673118000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-93000-8_47"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319929996","9783319930008"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-93000-8_47","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}