{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T14:31:56Z","timestamp":1773930716022,"version":"3.50.1"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T00:00:00Z","timestamp":1707696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T00:00:00Z","timestamp":1707696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1007\/s00371-024-03268-8","type":"journal-article","created":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T14:02:06Z","timestamp":1707746526000},"page":"8729-8745","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["StairNetV3: depth-aware stair modeling using deep learning"],"prefix":"10.1007","volume":"40","author":[{"given":"Chen","family":"Wang","sequence":"first","affiliation":[]},{"given":"Zhongcai","family":"Pei","sequence":"additional","affiliation":[]},{"given":"Shuang","family":"Qiu","sequence":"additional","affiliation":[]},{"given":"Yachun","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3974-1271","authenticated-orcid":false,"given":"Zhiyong","family":"Tang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,12]]},"reference":[{"key":"3268_CR1","doi-asserted-by":"publisher","unstructured":"Krausz, N.E., Hargrove, L.J.: Recognition of ascending stairs from 2d images for control of powered lower limb prostheses. In: 2015 7th International IEEE\/EMBS Conference on Neural Engineering (NER), pp. 615\u2013618 (2015). https:\/\/doi.org\/10.1109\/NER.2015.7146698","DOI":"10.1109\/NER.2015.7146698"},{"key":"3268_CR2","doi-asserted-by":"publisher","unstructured":"Murakami, S., Shimakawa, M., Kivota, K., Kato, T.: Study on stairs detection using RGB-depth images. In: 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS), pp. 1186\u20131191 (2014). https:\/\/doi.org\/10.1109\/SCIS-ISIS.2014.7044705","DOI":"10.1109\/SCIS-ISIS.2014.7044705"},{"key":"3268_CR3","doi-asserted-by":"publisher","unstructured":"Shahrabadi, S., Rodrigues, J.M., Buf, J.: Detection of indoor and outdoor stairs. In: Iberian Conference on Pattern Recognition & Image Analysis, pp. 847\u2013854 (2013). https:\/\/doi.org\/10.1007\/978-3-642-38628-2_100","DOI":"10.1007\/978-3-642-38628-2_100"},{"key":"3268_CR4","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","volume":"8","author":"J Canny","year":"1986","unstructured":"Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679\u2013698 (1986)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3268_CR5","unstructured":"Hough, P.V.C.: Method and Means for Recognizing Complex Patterns (1962)"},{"key":"3268_CR6","doi-asserted-by":"publisher","unstructured":"Westfechtel, T., Ohno, K., Mertsching, B., Nickchen, D., Kojima, S., Tadokoro, S.: 3d graph based stairway detection and localization for mobile robots. In: 2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 473\u2013479 (2016). https:\/\/doi.org\/10.1109\/IROS.2016.7759096","DOI":"10.1109\/IROS.2016.7759096"},{"key":"3268_CR7","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1016\/j.cviu.2016.04.007","volume":"154","author":"A Perez-Yus","year":"2017","unstructured":"Perez-Yus, A., Gutierrez-Gomez, D., Lopez-Nicolas, G., Guerrero, J.J.: Stairs detection with odometry-aided traversal from a wearable RGB-D camera. Comput. Vis. Image Underst. 154, 192\u2013205 (2017). https:\/\/doi.org\/10.1016\/j.cviu.2016.04.007","journal-title":"Comput. Vis. Image Underst."},{"key":"3268_CR8","doi-asserted-by":"publisher","unstructured":"Zhao, X., Chen, W., Yan, X., Wang, J., Wu, X.: Real-time stairs geometric parameters estimation for lower limb rehabilitation exoskeleton. In: 2018 Chinese Control And Decision Conference (CCDC), pp. 5018\u20135023 (2018). https:\/\/doi.org\/10.1109\/CCDC.2018.8408001","DOI":"10.1109\/CCDC.2018.8408001"},{"issue":"6","key":"3268_CR9","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981). https:\/\/doi.org\/10.1145\/358669.358692","journal-title":"Commun. ACM"},{"issue":"6","key":"3268_CR10","doi-asserted-by":"publisher","first-page":"403","DOI":"10.5573\/IEIESPC.2015.4.6.403","volume":"4","author":"KW Oh","year":"2015","unstructured":"Oh, K.W., Choi, K.S.: Supervoxel-based staircase detection from range data. IEIE Trans. Smart Process. Comput. 4(6), 403\u2013406 (2015). https:\/\/doi.org\/10.5573\/IEIESPC.2015.4.6.403","journal-title":"IEIE Trans. Smart Process. Comput."},{"key":"3268_CR11","doi-asserted-by":"publisher","unstructured":"Lee, J.-T., Kim, H.-U., Lee, C., Kim, C.-S.: Semantic line detection and its applications. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 3249\u20133257 (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.350","DOI":"10.1109\/ICCV.2017.350"},{"issue":"9","key":"3268_CR12","doi-asserted-by":"publisher","first-page":"4793","DOI":"10.1109\/TPAMI.2021.3077129","volume":"44","author":"K Zhao","year":"2022","unstructured":"Zhao, K., Han, Q., Zhang, C.-B., Xu, J., Cheng, M.-M.: Deep hough transform for semantic line detection. IEEE Trans. Pattern Anal. Mach. Intell. 44(9), 4793\u20134806 (2022). https:\/\/doi.org\/10.1109\/TPAMI.2021.3077129","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3268_CR13","doi-asserted-by":"publisher","unstructured":"Zhou, Y., Qi, H., Ma, Y.: End-to-end wireframe parsing. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 962\u2013971 (2019). https:\/\/doi.org\/10.1109\/ICCV.2019.00105","DOI":"10.1109\/ICCV.2019.00105"},{"key":"3268_CR14","doi-asserted-by":"publisher","unstructured":"Xue, N., Wu, T., Bai, S., Wang, F., Xia, G.-S., Zhang, L., Torr, P.H.S.: Holistically-attracted wireframe parsing. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2785\u20132794 (2020). https:\/\/doi.org\/10.1109\/CVPR42600.2020.00286","DOI":"10.1109\/CVPR42600.2020.00286"},{"key":"3268_CR15","doi-asserted-by":"publisher","unstructured":"Zhang, H., Luo, Y., Qin, F., He, Y., Liu, X.: Elsd: efficient line segment detector and descriptor. In: 2021 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 2949\u20132958 (2021). https:\/\/doi.org\/10.1109\/ICCV48922.2021.00296","DOI":"10.1109\/ICCV48922.2021.00296"},{"key":"3268_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neucom.2022.07.026","volume":"506","author":"X Dai","year":"2022","unstructured":"Dai, X., Gong, H., Wu, S., Yuan, X., Yi, M.: Fully convolutional line parsing. Neurocomputing 506, 1\u201311 (2022). https:\/\/doi.org\/10.1016\/j.neucom.2022.07.026","journal-title":"Neurocomputing"},{"key":"3268_CR17","doi-asserted-by":"publisher","unstructured":"Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision\u2014ECCV 2020, pp. 276\u2013291. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58586-0_17","DOI":"10.1007\/978-3-030-58586-0_17"},{"key":"3268_CR18","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1007\/s00371-021-02353-6","volume":"39","author":"M Haris","year":"2023","unstructured":"Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. Vis. Comput. 39, 519\u2013538 (2023). https:\/\/doi.org\/10.1007\/s00371-021-02353-6","journal-title":"Vis. Comput."},{"key":"3268_CR19","unstructured":"Platt, J.C.: Sequential minimal optimization: a fast algorithm for training support vector machines. In: Advances in Kernel Methods-Support Vector Learning, vol. 208 (1998)"},{"key":"3268_CR20","doi-asserted-by":"publisher","unstructured":"Khaliluzzaman, M., Yakub, M., Chakraborty, N.: Comparative analysis of stairways detection based on RGB and RGB-D image. In: 2018 International Conference on Innovations in Science, Engineering and Technology (ICISET), pp. 519\u2013524 (2018). https:\/\/doi.org\/10.1109\/ICISET.2018.8745624","DOI":"10.1109\/ICISET.2018.8745624"},{"key":"3268_CR21","doi-asserted-by":"publisher","unstructured":"Khaliluzzaman, M., Deb, K., Jo, K.-H.: Geometrical feature based stairways detection and recognition using depth sensor. In: IECON 2018\u201444th Annual Conference of the IEEE Industrial Electronics Society, pp. 3250\u20133255 (2018). https:\/\/doi.org\/10.1109\/IECON.2018.8591340","DOI":"10.1109\/IECON.2018.8591340"},{"key":"3268_CR22","unstructured":"Redmon, J., Farhadi, A.: YOLOv3: An Incremental Improvement (2018)"},{"key":"3268_CR23","doi-asserted-by":"publisher","unstructured":"Patil, U., Gujarathi, A., Kulkarni, A., Jain, A., Malke, L., Tekade, R., Paigwar, K., Chaturvedi, P.: Deep learning based stair detection and statistical image filtering for autonomous stair climbing. In: 2019 Third IEEE International Conference on Robotic Computing (IRC), pp. 159\u2013166 (2019). https:\/\/doi.org\/10.1109\/IRC.2019.00031","DOI":"10.1109\/IRC.2019.00031"},{"key":"3268_CR24","doi-asserted-by":"publisher","first-page":"16124","DOI":"10.1038\/s41598-022-20667-w","volume":"12","author":"C Wang","year":"2022","unstructured":"Wang, C., Pei, Z., Shuang, Q., Tang, Z.: Deep leaning-based ultra-fast stair detection. Sci. Rep. 12, 16124 (2022). https:\/\/doi.org\/10.1038\/s41598-022-20667-w","journal-title":"Sci. Rep."},{"key":"3268_CR25","doi-asserted-by":"publisher","DOI":"10.3390\/s23042175","author":"C Wang","year":"2023","unstructured":"Wang, C., Pei, Z., Qiu, S., Tang, Z.: RGB-D-based stair detection and estimation using deep learning. Sensors (2023). https:\/\/doi.org\/10.3390\/s23042175","journal-title":"Sensors"},{"key":"3268_CR26","doi-asserted-by":"publisher","unstructured":"Huang, X., Tang, Z.: Staircase detection algorithm based on projection-histogram. In: 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), pp. 1130\u20131133 (2018). Doi: https:\/\/doi.org\/10.1109\/IMCEC.2018.8469186","DOI":"10.1109\/IMCEC.2018.8469186"},{"key":"3268_CR27","doi-asserted-by":"publisher","unstructured":"Carbonara, S., Guaragnella, C.: Efficient stairs detection algorithm assisted navigation for vision impaired people. In: 2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings, pp. 313\u2013318 (2014). https:\/\/doi.org\/10.1109\/INISTA.2014.6873637","DOI":"10.1109\/INISTA.2014.6873637"},{"key":"3268_CR28","doi-asserted-by":"publisher","unstructured":"Khaliluzzaman, M., Deb, K., Jo, K.-H.: Stairways detection and distance estimation approach based on three connected point and triangular similarity. In: 2016 9th International Conference on Human System Interactions (HSI), pp. 330\u2013336 (2016). https:\/\/doi.org\/10.1109\/HSI.2016.7529653","DOI":"10.1109\/HSI.2016.7529653"},{"key":"3268_CR29","doi-asserted-by":"crossref","unstructured":"Diamantis, D.E., Koutsiou, D.C.C., Iakovidis, D.K.: Staircase detection using a lightweight look-behind fully convolutional neural network. In: Macintyre, J., Iliadis, L., Maglogiannis, I., Jayne, C. (eds.) Engineering Applications of Neural Networks, pp. 522\u2013532. Springer, Cham (2019)","DOI":"10.1007\/978-3-030-20257-6_45"},{"key":"3268_CR30","unstructured":"Lee, Y.H., Leung, T.-S., Medioni, G.: Real-time staircase detection from a wearable stereo system. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp. 3770\u20133773 (2012)"},{"key":"3268_CR31","doi-asserted-by":"publisher","unstructured":"Rekhawar, N., Govindani, Y., Rao, N.: Deep learning based detection, segmentation and vision based pose estimation of staircase. In: 2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS), pp. 78\u201383 (2022). https:\/\/doi.org\/10.1109\/PCEMS55161.2022.9807915","DOI":"10.1109\/PCEMS55161.2022.9807915"},{"key":"3268_CR32","unstructured":"Glenn, J.: yolov5 (2019). https:\/\/github.com\/ultralytics\/yolov5"},{"key":"3268_CR33","doi-asserted-by":"publisher","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2015, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"3268_CR34","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"issue":"2","key":"3268_CR35","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.jvcir.2013.11.005","volume":"25","author":"S Wang","year":"2014","unstructured":"Wang, S., Pan, H., Zhang, C., Tian, Y.: RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs. J. Vis. Commun. Image Represent. 25(2), 263\u2013272 (2014). https:\/\/doi.org\/10.1016\/j.jvcir.2013.11.005","journal-title":"J. Vis. Commun. Image Represent."},{"key":"3268_CR36","doi-asserted-by":"publisher","unstructured":"Wang, S., Tian, Y.: Detecting stairs and pedestrian crosswalks for the blind by RGBD camera. In: 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, pp. 732\u2013739 (2012). https:\/\/doi.org\/10.1109\/BIBMW.2012.6470227","DOI":"10.1109\/BIBMW.2012.6470227"},{"key":"3268_CR37","doi-asserted-by":"publisher","unstructured":"Munoz, R., Rong, X., Tian, Y.: Depth-aware indoor staircase detection and recognition for the visually impaired. In: 2016 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pp. 1\u20136 (2016). https:\/\/doi.org\/10.1109\/ICMEW.2016.7574706","DOI":"10.1109\/ICMEW.2016.7574706"},{"key":"3268_CR38","doi-asserted-by":"publisher","unstructured":"P\u00e9rez-Yus, A., L\u00f3pez-Nicol\u00e1s, G., Guerrero, J.J.: Detection and modelling of staircases using a wearable depth sensor. In: Agapito, L., Bronstein, M.M., Rother, C. (eds.) Computer Vision\u2014ECCV 2014 Workshops, pp. 449\u2013463. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-16199-0_32","DOI":"10.1007\/978-3-319-16199-0_32"},{"issue":"4","key":"3268_CR39","doi-asserted-by":"publisher","first-page":"124","DOI":"10.13382\/j.jemi.B1902746","volume":"34","author":"Y Yifei","year":"2020","unstructured":"Yifei, Y., Jianzhong, W.: Stair area recognition in complex environment based on point cloud. J. Electron. Meas. Instrum. 34(4), 124\u2013133 (2020). https:\/\/doi.org\/10.13382\/j.jemi.B1902746","journal-title":"J. Electron. Meas. Instrum."},{"key":"3268_CR40","doi-asserted-by":"publisher","first-page":"56249","DOI":"10.1109\/ACCESS.2022.3178154","volume":"10","author":"H Matsumura","year":"2022","unstructured":"Matsumura, H., Premachandra, C.: Deep-learning-based stair detection using 3d point cloud data for preventing walking accidents of the visually impaired. IEEE Access 10, 56249\u201356255 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3178154","journal-title":"IEEE Access"},{"key":"3268_CR41","doi-asserted-by":"publisher","unstructured":"Charles, R.Q., Su, H., Kaichun, M., Guibas, L.J.: Pointnet: deep learning on point sets for 3d classification and segmentation. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 77\u201385 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.16","DOI":"10.1109\/CVPR.2017.16"},{"key":"3268_CR42","doi-asserted-by":"publisher","first-page":"2691","DOI":"10.1007\/s00371-021-02147-w","volume":"38","author":"C Zatout","year":"2022","unstructured":"Zatout, C., Larabi, S.: Semantic scene synthesis: application to assistive systems. Vis. Comput. 38, 2691\u20132705 (2022). https:\/\/doi.org\/10.1007\/s00371-021-02147-w","journal-title":"Vis. Comput."},{"key":"3268_CR43","doi-asserted-by":"publisher","unstructured":"Zatout, C., Larabi, S., Mendili, I., Barnab\u00e9, S.A.E.: Ego-semantic labeling of scene from depth image for visually impaired and blind people. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 4376\u20134384 (2019). https:\/\/doi.org\/10.1109\/ICCVW.2019.00538","DOI":"10.1109\/ICCVW.2019.00538"},{"key":"3268_CR44","unstructured":"Zhou, X., Wang, D., Kr\u00e4henb\u00fchl, P.: Objects as Points (2019)"},{"issue":"8","key":"3268_CR45","doi-asserted-by":"publisher","first-page":"2011","DOI":"10.1109\/TPAMI.2019.2913372","volume":"42","author":"J Hu","year":"2020","unstructured":"Hu, J., Shen, L., Albanie, S., Sun, G., Wu, E.: Squeeze-and-excitation networks. IEEE Trans. Pattern Anal. Mach. Intell. 42(8), 2011\u20132023 (2020). https:\/\/doi.org\/10.1109\/TPAMI.2019.2913372","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3268_CR46","doi-asserted-by":"publisher","unstructured":"Xie, S., Girshick, R., Doll\u00e1r, P., Tu, Z., He, K.: Aggregated residual transformations for deep neural networks. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5987\u20135995 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.634","DOI":"10.1109\/CVPR.2017.634"},{"key":"3268_CR47","doi-asserted-by":"publisher","unstructured":"Wang, C., Pei, Z., Qiu, S., Tang, Z.: Stair dataset with depth maps. Mendeley Data (2023). https:\/\/doi.org\/10.17632\/p28ncjnvgk.2","DOI":"10.17632\/p28ncjnvgk.2"},{"key":"3268_CR48","unstructured":"Intel: Depth Camera D435i. https:\/\/www.intelrealsense.com\/depth-camera-d435i\/"},{"key":"3268_CR49","doi-asserted-by":"publisher","DOI":"10.17632\/6kffmjt7g2.1","author":"C Wang","year":"2023","unstructured":"Wang, C., Pei, Z., Qiu, S., Wang, Y., Tang, Z.: RGB-D stair dataset. Mendeley Data (2023). https:\/\/doi.org\/10.17632\/6kffmjt7g2.1","journal-title":"Mendeley Data"},{"key":"3268_CR50","first-page":"1","volume":"9","author":"A Garcia-Garcia","year":"2017","unstructured":"Garcia-Garcia, A., Orts-Escolano, S., Oprea, S., Villena-Martinez, V., Garcia-Rodriguez, J.: A review on deep learning techniques. Appl. Semant. Segm. 9, 1\u20137 (2017)","journal-title":"Appl. Semant. Segm."},{"key":"3268_CR51","unstructured":"Kingma, D.P., Ba, J.: Adam: A Method for Stochastic Optimization (2017)"},{"key":"3268_CR52","unstructured":"Howard, A.G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., Adam, H.: MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications (2017)"},{"key":"3268_CR53","unstructured":"Zhou, Q.-Y., Park, J., Koltun, V.: Open3D: a modern library for 3D data processing. arXiv:1801.09847 (2018)"},{"key":"3268_CR54","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03268-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-024-03268-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03268-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T09:10:58Z","timestamp":1731402658000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-024-03268-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,12]]},"references-count":54,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["3268"],"URL":"https:\/\/doi.org\/10.1007\/s00371-024-03268-8","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,12]]},"assertion":[{"value":"4 January 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 February 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}