{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T15:48:53Z","timestamp":1768232933103,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":31,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557547","type":"print"},{"value":"9789819557554","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-5755-4_3","type":"book-chapter","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T12:30:34Z","timestamp":1768221034000},"page":"39-53","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DMDet: Dynamic Multi-modal Object Detection Network for UAV Aerial Imagery"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6003-1930","authenticated-orcid":false,"given":"Jianqiang","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4980-0343","authenticated-orcid":false,"given":"Zhe","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5539-2599","authenticated-orcid":false,"given":"Ziying","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,13]]},"reference":[{"issue":"6","key":"3_CR1","doi-asserted-by":"publisher","first-page":"2934","DOI":"10.3390\/s23062934","volume":"23","author":"C Bao","year":"2023","unstructured":"Bao, C., Cao, J., Hao, Q., Cheng, Y., Ning, Y., Zhao, T.: Dual-yolo architecture from infrared and visible images for object detection. Sensors 23(6), 2934 (2023)","journal-title":"Sensors"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Chen, Y., Wang, B., Guo, X., Zhu, W., He, J., Liu, X., Yuan, J.: Deyolo: dual-feature-enhancement yolo for cross-modality object detection. In: International Conference on Pattern Recognition. pp. 236\u2013252. Springer (2025)","DOI":"10.1007\/978-3-031-78447-7_16"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Ding, J., Xue, N., Long, Y., Xia, G.S., Lu, Q.: Learning roi transformer for oriented object detection in aerial images. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp. 2849\u20132858 (2019)","DOI":"10.1109\/CVPR.2019.00296"},{"key":"3_CR4","doi-asserted-by":"publisher","unstructured":"Fu, H., Liu, H., Yuan, J., He, X., Lin, J., Li, Z.: Yolo-adaptor: a fast adaptive one-stage detector for non-aligned visible-infrared object detection. IEEE Trans. Intell. Vehicles 1\u201314 (2024). https:\/\/doi.org\/10.1109\/TIV.2024.3393015","DOI":"10.1109\/TIV.2024.3393015"},{"issue":"2","key":"3_CR5","doi-asserted-by":"publisher","first-page":"539","DOI":"10.3390\/rs15020539","volume":"15","author":"I Gallo","year":"2023","unstructured":"Gallo, I., Rehman, A.U., Dehkordi, R.H., Landro, N., La Grassa, R., Boschetti, M.: Deep object detection of crop weeds: performance of yolov7 on a real case dataset from uav images. Remote Sens. 15(2), 539 (2023)","journal-title":"Remote Sens."},{"key":"3_CR6","first-page":"1","volume":"60","author":"J Han","year":"2021","unstructured":"Han, J., Ding, J., Li, J., Xia, G.S.: Align deep features for oriented object detection. IEEE Trans. Geosci. Remote Sens. 60, 1\u201311 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Han, J., Ding, J., Xue, N., Xia, G.S.: Redet: a rotation-equivariant detector for aerial object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 2786\u20132795 (2021)","DOI":"10.1109\/CVPR46437.2021.00281"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"He, X., Tang, C., Zou, X., Zhang, W.: Multispectral object detection via cross-modal conflict-aware learning. In: Proceedings of the 31st ACM International Conference on Multimedia. pp. 1465\u20131474 (2023)","DOI":"10.1145\/3581783.3612651"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Hu, Y., Shi, L., Yao, L., Weng, L.: Dual attention feature fusion for visible-infrared object detection. In: International Conference on Artificial Neural Networks. pp. 53\u201365. Springer (2023)","DOI":"10.1007\/978-3-031-44195-0_5"},{"key":"3_CR10","unstructured":"Jocher, G., Qiu, J.: Ultralytics yolo11 (2024). https:\/\/github.com\/ultralytics\/ultralytics"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., Lo, W.Y., et\u00a0al.: Segment anything. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp. 4015\u20134026 (2023)","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"3_CR12","first-page":"1","volume":"61","author":"Y Mo","year":"2023","unstructured":"Mo, Y., Kang, X., Zhang, S., Duan, P., Li, S.: A robust infrared and visible image registration method for dual-sensor UAV system. IEEE Trans. Geosci. Remote Sens. 61, 1\u201313 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108786","volume":"130","author":"F Qingyun","year":"2022","unstructured":"Qingyun, F., Zhaokui, W.: Cross-modality attentive feature fusion for object detection in multispectral remote sensing imagery. Pattern Recogn. 130, 108786 (2022)","journal-title":"Pattern Recogn."},{"key":"3_CR14","unstructured":"Ravi, N., Gabeur, V., Hu, Y.T., Hu, R., Ryali, C., Ma, T., Khedr, H., R\u00e4dle, R., Rolland, C., Gustafson, L., Mintun, E., Pan, J., Alwala, K.V., Carion, N., Wu, C.Y., Girshick, R., Doll\u00e1r, P., Feichtenhofer, C.: Sam 2: segment anything in images and videos (2024). arXiv preprint arXiv:2408.00714, https:\/\/arxiv.org\/abs\/2408.00714"},{"issue":"6","key":"3_CR15","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3_CR16","unstructured":"Ross, T.Y., Doll\u00e1r, G.: Focal loss for dense object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 2980\u20132988 (2017)"},{"key":"3_CR17","unstructured":"Sun, W., Dai, L., Zhang, X., Chang, P., He, X.: Rsod: Real-time small object detection algorithm in UAV-based traffic monitoring. Appl. Intell. 1\u201316 (2022)"},{"key":"3_CR18","doi-asserted-by":"crossref","unstructured":"Sun, Y., Cao, B., Zhu, P., Hu, Q.: Detfusion: a detection-driven infrared and visible image fusion network. In: Proceedings of the 30th ACM International Conference on Multimedia. pp. 4003\u20134011 (2022)","DOI":"10.1145\/3503161.3547902"},{"issue":"10","key":"3_CR19","doi-asserted-by":"publisher","first-page":"6700","DOI":"10.1109\/TCSVT.2022.3168279","volume":"32","author":"Y Sun","year":"2022","unstructured":"Sun, Y., Cao, B., Zhu, P., Hu, Q.: Drone-based rgb-infrared cross-modality vehicle detection via uncertainty-aware learning. IEEE Trans. Circuits Syst. Video Technol. 32(10), 6700\u20136713 (2022). https:\/\/doi.org\/10.1109\/TCSVT.2022.3168279","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Wang, H., Wang, C., Fu, Q., Si, B., Zhang, D., Kou, R., Yu, Y., Feng, C.: Yolofiv: Object detection algorithm for around-the-clock aerial remote sensing images by fusing infrared and visible features. IEEE J. Selected Topics Appl. Earth Observ. Remote Sens. (2024)","DOI":"10.1109\/JSTARS.2024.3447649"},{"key":"3_CR21","doi-asserted-by":"crossref","unstructured":"Xia, Z., Pan, X., Song, S., Li, L.E., Huang, G.: Vision transformer with deformable attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4794\u20134803 (2022)","DOI":"10.1109\/CVPR52688.2022.00475"},{"key":"3_CR22","doi-asserted-by":"publisher","first-page":"8933","DOI":"10.1109\/JSTARS.2023.3315544","volume":"16","author":"J Xie","year":"2023","unstructured":"Xie, J., Nie, J., Ding, B., Yu, M., Cao, J.: Cross-modal local calibration and global context modeling network for rgb-infrared remote-sensing object detection. IEEE J. Selected Topics Appl. Earth Observ. Remote Sens. 16, 8933\u20138942 (2023)","journal-title":"IEEE J. Selected Topics Appl. Earth Observ. Remote Sens."},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Xie, X., Cheng, G., Wang, J., Yao, X., Han, J.: Oriented R-CNN for object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp. 3520\u20133529 (2021)","DOI":"10.1109\/ICCV48922.2021.00350"},{"key":"3_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2024.102246","volume":"105","author":"M Yuan","year":"2024","unstructured":"Yuan, M., Shi, X., Wang, N., Wang, Y., Wei, X.: Improving rgb-infrared object detection with cascade alignment-guided transformer. Inform. Fusion 105, 102246 (2024)","journal-title":"Inform. Fusion"},{"key":"3_CR25","doi-asserted-by":"crossref","unstructured":"Yuan, M., Wang, Y., Wei, X.: Translation, scale and rotation: cross-modal alignment meets rgb-infrared vehicle detection. In: European Conference on Computer Vision. pp. 509\u2013525. Springer (2022)","DOI":"10.1007\/978-3-031-20077-9_30"},{"key":"3_CR26","unstructured":"Yuan, M., Wei, X.: C 2 former: calibrated and complementary transformer for rgb-infrared object detection. IEEE Trans. Geosci. Remote Sens. (2024)"},{"key":"3_CR27","first-page":"1","volume":"61","author":"J Zhang","year":"2023","unstructured":"Zhang, J., Lei, J., Xie, W., Fang, Z., Li, Y., Du, Q.: Superyolo: super resolution assisted object detection in multimodal remote sensing imagery. IEEE Trans. Geosci. Remote Sens. 61, 1\u201315 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3_CR28","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.inffus.2018.09.015","volume":"50","author":"L Zhang","year":"2019","unstructured":"Zhang, L., Liu, Z., Zhang, S., Yang, X., Qiao, H., Huang, K., Hussain, A.: Cross-modality interactive attention network for multispectral pedestrian detection. Inform. Fusion 50, 20\u201329 (2019)","journal-title":"Inform. Fusion"},{"key":"3_CR29","unstructured":"Zhang, L., Liu, Z., Zhu, X., Song, Z., Yang, X., Lei, Z., Qiao, H.: Weakly aligned feature fusion for multimodal object detection. IEEE Trans. Neural Netw. Learn. Syst. (2021)"},{"key":"3_CR30","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1007\/978-3-030-58523-5_46","volume-title":"Computer Vision\u2014ECCV 2020","author":"K Zhou","year":"2020","unstructured":"Zhou, K., Chen, L., Cao, X.: Improving multispectral pedestrian detection by addressing modality imbalance problems. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12363, pp. 787\u2013803. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58523-5_46"},{"key":"3_CR31","unstructured":"Zhu, X., Su, W., Lu, L., Li, B., Wang, X., Dai, J.: Deformable DETR: deformable transformers for end-to-end object detection (2020). arXiv preprint arXiv:2010.04159"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5755-4_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T12:30:54Z","timestamp":1768221054000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5755-4_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557547","9789819557554"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5755-4_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"13 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}