{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T06:26:35Z","timestamp":1774679195418,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819698622","type":"print"},{"value":"9789819698639","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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\/978-981-96-9863-9_5","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T14:39:19Z","timestamp":1753281559000},"page":"53-64","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["DBTNet: Dual-Stream Background-Target Decoupling Network for Infrared Small Target Detection"],"prefix":"10.1007","author":[{"given":"Xianmin","family":"Lan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"issue":"5","key":"5_CR1","doi-asserted-by":"publisher","first-page":"3737","DOI":"10.1109\/TGRS.2020.3022069","volume":"59","author":"Y Sun","year":"2021","unstructured":"Sun, Y., Yang, J., An, W.: Infrared dim and small target detection via multiple subspace learning and spatial-temporal patch-tensor model. IEEE Trans. Geosci. Remote Sens. 59(5), 3737\u20133752 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Teutsch, M., Kr\u00fcger, W.: Classification of small boats in infrared images for maritime surveillance. In: 2010 International WaterSide Security Conference, pp. 1\u20137. IEEE (2010)","DOI":"10.1109\/WSSC.2010.5730289"},{"key":"5_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2021.103659","volume":"114","author":"M Ju","year":"2021","unstructured":"Ju, M., Luo, J., Liu, G., et al.: ISTDet: an efficient end-to-end neural network for infrared small target detection. Infrared Phys. Technol. 114, 103659 (2021)","journal-title":"Infrared Phys. Technol."},{"key":"5_CR4","doi-asserted-by":"publisher","first-page":"4150","DOI":"10.1109\/JSTARS.2021.3069032","volume":"14","author":"W Xue","year":"2021","unstructured":"Xue, W., Qi, J., Shao, G., et al.: Low-rank approximation and multiple sparse constraint modeling for infrared low-flying fixed-wing UAV detection. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 14, 4150\u20134166 (2021)","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"5_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109788","volume":"143","author":"R Kou","year":"2023","unstructured":"Kou, R., Wang, C., Peng, Z., et al.: Infrared small target segmentation networks: a survey. Pattern Recogn. 143, 109788 (2023)","journal-title":"Pattern Recogn."},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Ying, X., Liu, L., Wang, Y., et al.: Mapping degeneration meets label evolution: learning infrared small target detection with single point supervision. In: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 15528\u201315538. IEEE, Vancouver (2023)","DOI":"10.1109\/CVPR52729.2023.01490"},{"key":"5_CR7","first-page":"1","volume":"60","author":"K Wang","year":"2022","unstructured":"Wang, K., Du, S., Liu, C., et al.: Interior attention-aware network for infrared small target detection. IEEE Trans. Geosci. Remote Sens. 60, 1\u201313 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"6","key":"5_CR8","doi-asserted-by":"publisher","first-page":"2145","DOI":"10.1016\/j.patcog.2009.12.023","volume":"43","author":"X Bai","year":"2010","unstructured":"Bai, X., Zhou, F.: Analysis of new top-hat transformation and the application for infrared dim small target detection. Pattern Recogn. 43(6), 2145\u20132156 (2010)","journal-title":"Pattern Recogn."},{"key":"5_CR9","doi-asserted-by":"crossref","unstructured":"Deshpande, S.D., Meng, H., Ronda, V.: et al.: Max-mean and max-median filters for detection of small targets. In: Signal and Data Processing of Small Targets 1999, pp. 74\u201383 (1999)","DOI":"10.1117\/12.364049"},{"issue":"9","key":"5_CR10","doi-asserted-by":"publisher","first-page":"1670","DOI":"10.1109\/LGRS.2020.3004978","volume":"18","author":"J Han","year":"2021","unstructured":"Han, J., Moradi, S., Faramarzi, I., et al.: Infrared small target detection based on the weighted strengthened local contrast measure. IEEE Geosci. Remote Sens. Lett. 18(9), 1670\u20131674 (2021)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"10","key":"5_CR11","doi-asserted-by":"publisher","first-page":"1822","DOI":"10.1109\/LGRS.2019.2954578","volume":"17","author":"J Han","year":"2020","unstructured":"Han, J., Moradi, S., Faramarzi, I., et al.: A local contrast method for infrared small-target detection utilizing a tri-layer window. IEEE Geosci. Remote Sens. Lett. 17(10), 1822\u20131826 (2020)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"12","key":"5_CR12","doi-asserted-by":"publisher","first-page":"4996","DOI":"10.1109\/TIP.2013.2281420","volume":"22","author":"C Gao","year":"2013","unstructured":"Gao, C., Meng, D., Yang, Y., et al.: Infrared patch-image model for small target detection in a single image. IEEE Trans. Image Process. 22(12), 4996\u20135009 (2013)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"5_CR13","doi-asserted-by":"publisher","first-page":"382","DOI":"10.3390\/rs11040382","volume":"11","author":"L Zhang","year":"2019","unstructured":"Zhang, L., Peng, Z.: Infrared small target detection based on partial sum of the tensor nuclear norm. Remote Sens. 11(4), 382 (2019)","journal-title":"Remote Sens."},{"key":"5_CR14","first-page":"1","volume":"62","author":"S Yuan","year":"2024","unstructured":"Yuan, S., Qin, H., Yan, X., et al.: SCTransNet: spatial-channel cross transformer network for infrared small target detection. IEEE Trans. Geosci. Remote Sens. 62, 1\u201315 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Dai, Y., Wu, Y., Zhou, F., et al.: Asymmetric contextual modulation for infrared small target detection. In: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 949\u2013958. IEEE (2021)","DOI":"10.1109\/WACV48630.2021.00099"},{"key":"5_CR16","doi-asserted-by":"publisher","first-page":"1745","DOI":"10.1109\/TIP.2022.3199107","volume":"32","author":"B Li","year":"2023","unstructured":"Li, B., Xiao, C., Wang, L., et al.: Dense nested attention network for infrared small target detection. IEEE Trans. Image Process. 32, 1745\u20131758 (2023)","journal-title":"IEEE Trans. Image Process."},{"key":"5_CR17","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1109\/TIP.2022.3228497","volume":"32","author":"X Wu","year":"2023","unstructured":"Wu, X., Hong, D., Chanussot, J.: UIU-Net: U-Net in U-Net for infrared small object detection. IEEE Trans. Image Process. 32, 364\u2013376 (2023)","journal-title":"IEEE Trans. Image Process."},{"issue":"14","key":"5_CR18","doi-asserted-by":"publisher","first-page":"3258","DOI":"10.3390\/rs14143258","volume":"14","author":"G Chen","year":"2022","unstructured":"Chen, G., Wang, W., Tan, S.: IRSTFormer: a hierarchical vision transformer for infrared small target detection. Remote Sens. 14(14), 3258 (2022)","journal-title":"Remote Sens."},{"key":"5_CR19","doi-asserted-by":"publisher","first-page":"5921","DOI":"10.1109\/TIP.2023.3326396","volume":"32","author":"F Liu","year":"2023","unstructured":"Liu, F., Gao, C., Chen, F., et al.: Infrared small and dim target detection with transformer under complex backgrounds. IEEE Trans. Image Process. 32, 5921\u20135932 (2023)","journal-title":"IEEE Trans. Image Process."},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Liu, Q., Liu, R., Zheng, B., et al.: Infrared small target detection with scale and location sensitivity. In: 2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 17490\u201317499. IEEE, Seattle (2024)","DOI":"10.1109\/CVPR52733.2024.01656"},{"issue":"4","key":"5_CR21","doi-asserted-by":"publisher","first-page":"4250","DOI":"10.1109\/TAES.2023.3238703","volume":"59","author":"T Zhang","year":"2023","unstructured":"Zhang, T., Li, L., Cao, S., et al.: Attention-guided pyramid context networks for detecting infrared small target under complex background. IEEE Trans. Aerosp. Electron. Syst. 59(4), 4250\u20134261 (2023)","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"5_CR22","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., et al.: CBAM: convolutional block attention module. In: Proceedings European Conference on Computer Vision (ECCV), pp. 3\u201319. Springer, Munich (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"5_CR23","doi-asserted-by":"crossref","unstructured":"Liu, W., Lu, H., Fu, H., Cao, Z.: Learning to upsample by learning to sample. In: 2023 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 6004\u20136014. IEEE, Paris (2023)","DOI":"10.1109\/ICCV51070.2023.00554"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7132\u20137141. IEEE, Salt Lake City (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"5_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhang, R., Yang, Y., et al.: ISNet: shape matters for infrared small target detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 877\u2013886. IEEE, New Orleans (2022)","DOI":"10.1109\/CVPR52688.2022.00095"},{"issue":"11","key":"5_CR26","doi-asserted-by":"publisher","first-page":"9813","DOI":"10.1109\/TGRS.2020.3044958","volume":"59","author":"Y Dai","year":"2021","unstructured":"Dai, Y., Wu, Y., Zhou, F., et al.: Attentional local contrast networks for infrared small target detection. IEEE Trans. Geosci. Remote Sens. 59(11), 9813\u20139824 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"5_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2024.115595","volume":"240","author":"D Zang","year":"2025","unstructured":"Zang, D., Su, W., Zhang, B., et al.: DCANet: dense convolutional attention network for infrared small target detection. Measurement 240, 115595 (2025)","journal-title":"Measurement"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9863-9_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T04:09:59Z","timestamp":1774670999000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9863-9_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698622","9789819698639"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9863-9_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"24 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","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":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}