{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T16:24:06Z","timestamp":1747153446122,"version":"3.40.5"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031801389"},{"type":"electronic","value":"9783031801396"}],"license":[{"start":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T00:00:00Z","timestamp":1732924800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T00:00:00Z","timestamp":1732924800000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-80139-6_3","type":"book-chapter","created":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T13:04:10Z","timestamp":1732885450000},"page":"30-45","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ICPR 2024 Competition on\u00a0Rider Intention Prediction"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4448-5794","authenticated-orcid":false,"given":"Shankar","family":"Gangisetty","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4465-7066","authenticated-orcid":false,"given":"Abdul","family":"Wasi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7448-2271","authenticated-orcid":false,"given":"Shyam Nandan","family":"Rai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6767-7057","authenticated-orcid":false,"given":"C. V.","family":"Jawahar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sajay","family":"Raj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manish","family":"Prajapati","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayesha","family":"Choudhary","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aaryadev","family":"Chandra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dev","family":"Chandan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shireen","family":"Chand","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suvaditya","family":"Mukherjee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,30]]},"reference":[{"key":"3_CR1","unstructured":"Swarajaya (2023). https:\/\/swarajyamag.com\/infrastructure\/two-wheelers-responsible-for-maximum-road-fatalities-in-india-killed-28-per-cent-pedestrians-last-year-report. Accessed 16 Feb 2024"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Aliakbarian, M.S., Saleh, F.S., Salzmann, M., Fernando, B., Petersson, L., Andersson, L.: VIENA2: a driving anticipation dataset (2018)","DOI":"10.1007\/978-3-030-20887-5_28"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, M.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002)","DOI":"10.1613\/jair.953"},{"key":"3_CR4","unstructured":"Dao, T., Gu, A.: Transformers are SSMs: generalized models and efficient algorithms through structured state space duality. ArXiv (2024)"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Gebert, P., Roitberg, A., Haurilet, M., Stiefelhagen, R.: End-to-end prediction of driver intention using 3D convolutional neural networks. In: IEEE IV (2019)","DOI":"10.1109\/IVS.2019.8814249"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"4","key":"3_CR7","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/5254.708428","volume":"13","author":"M Hearst","year":"1998","unstructured":"Hearst, M., Dumais, S., Osuna, E., Platt, J., Scholkopf, B.: Support vector machines. IEEE Intell. Syst. Appl. 13(4), 18\u201328 (1998)","journal-title":"IEEE Intell. Syst. Appl."},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Jain, A., Koppula, H.S., Soh, S., Raghavan, B., Saxena, A.: Car that knows before you do: anticipating maneuvers via learning temporal driving models. In: ICCV (2015)","DOI":"10.1109\/ICCV.2015.364"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Jain, A., Singh, A., Koppula, H.S., Soh, S., Saxena, A.: Recurrent neural networks for driver activity anticipation via sensory-fusion architecture. In: ICRA (2016)","DOI":"10.1109\/ICRA.2016.7487478"},{"key":"3_CR10","unstructured":"Kelshikar., T.: More and more 2-wheeler riders and pedestrians dying on Indian roads (2022). https:\/\/www.renewbuy.com\/articles\/general\/risks-must-know-before-riding-two-wheeler-in-india. Accessed 16 Feb 2024"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Khairdoost, N., Shirpour, M., Bauer, M.A., Beauchemin, S.S.: Real-time driver maneuver prediction using LSTM. IEEE Trans. Intell. Veh. (2020)","DOI":"10.1109\/TIV.2020.3003889"},{"key":"3_CR12","unstructured":"Laura Wood: Businesswire (2022). https:\/\/www.businesswire.com\/news\/home\/20220509005442\/en\/The-Global-Autonomous-Vehicle-Market-Will-Grow-to-2161.79-billion-by-2030-at-a-CAGR-of-40.1---ResearchAndMarkets.com. Accessed 16 Feb 2024"},{"key":"3_CR13","doi-asserted-by":"crossref","unstructured":"Ramanishka, V., Chen, Y.T., Misu, T., Saenko, K.: Toward driving scene understanding: a dataset for learning driver behavior and causal reasoning. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00803"},{"key":"3_CR14","doi-asserted-by":"crossref","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: ICLR (2015)","DOI":"10.1109\/ICCV.2015.314"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Tran, D., Wang, H., Torresani, L., Ray, J., LeCun, Y., Paluri, M.: A closer look at spatiotemporal convolutions for action recognition. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00675"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition. Competitions"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-80139-6_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T09:18:14Z","timestamp":1733131094000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-80139-6_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,30]]},"ISBN":["9783031801389","9783031801396"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-80139-6_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,30]]},"assertion":[{"value":"30 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}