{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T13:33:53Z","timestamp":1769261633681,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557639","type":"print"},{"value":"9789819557646","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\/978-981-95-5764-6_28","type":"book-chapter","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T06:08:23Z","timestamp":1769148503000},"page":"410-423","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DCAPNet: A Contrast-Enhanced and\u00a0Multi-scale Feature Fusion Network for\u00a0Infrared Small Target Detection"],"prefix":"10.1007","author":[{"given":"Yingying","family":"Gao","sequence":"first","affiliation":[]},{"given":"Maoyong","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xuedong","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Deng","sequence":"additional","affiliation":[]},{"given":"Mingli","family":"Dong","sequence":"additional","affiliation":[]},{"given":"Lianqing","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,24]]},"reference":[{"issue":"7","key":"28_CR1","doi-asserted-by":"publisher","first-page":"4204","DOI":"10.1109\/TGRS.2016.2538295","volume":"54","author":"H Deng","year":"2016","unstructured":"Deng, H., Sun, X., Liu, M., Ye, C., Zhou, X.: Small infrared target detection based on weighted local difference measure. IEEE Trans. Geosci. Remote Sens. 54(7), 4204\u20134214 (2016)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"28_CR2","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1080\/17686733.2023.2294598","volume":"22","author":"K Raghavan","year":"2025","unstructured":"Raghavan, K., Balasubramanian, S., Veezhinathan, K.: IR-GAN: improved generative adversarial networks for infrared breast image segmentation. Quant. Infrared Thermogr. J. 22(1), 70\u201396 (2025)","journal-title":"Quant. Infrared Thermogr. J."},{"key":"28_CR3","doi-asserted-by":"publisher","first-page":"47860","DOI":"10.1109\/ACCESS.2025.3550895","volume":"13","author":"D Sheng","year":"2025","unstructured":"Sheng, D., Jin, W., Wang, M., Yang, J.: Region-based self-segmentation guided diffusion model for thermal infrared to pseudo-color visible light image conversion. IEEE Access 13, 47860\u201347873 (2025)","journal-title":"IEEE Access"},{"issue":"6","key":"28_CR4","doi-asserted-by":"publisher","first-page":"16485","DOI":"10.1007\/s11042-023-15327-8","volume":"83","author":"KI Danaci","year":"2024","unstructured":"Danaci, K.I., Akagunduz, E.: A survey on infrared image & video sets. Multimed. Tools Appl. 83(6), 16485\u201316523 (2024)","journal-title":"Multimed. Tools Appl."},{"issue":"1","key":"28_CR5","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/j.infrared.2005.04.006","volume":"48","author":"M Zeng","year":"2006","unstructured":"Zeng, M., Li, J., Peng, Z.: The design of top-hat morphological filter and application to infrared target detection. Infrared Phys. Technol. 48(1), 67\u201376 (2006)","journal-title":"Infrared Phys. Technol."},{"key":"28_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2024.105346","volume":"139","author":"X Gao","year":"2024","unstructured":"Gao, X., et al.: Infrared small target detection algorithm based on filter kernel combination optimization learning method. Infrared Phys. Technol. 139, 105346 (2024)","journal-title":"Infrared Phys. Technol."},{"issue":"4","key":"28_CR7","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1145\/2010324.1964963","volume":"30","author":"S Paris","year":"2011","unstructured":"Paris, S., Hasinoff, S.W., Kautz, J.: Local laplacian filters: edge-aware image processing with a Laplacian pyramid. ACM Trans. Graph. 30(4), 68 (2011)","journal-title":"ACM Trans. Graph."},{"issue":"1","key":"28_CR8","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1109\/TGRS.2013.2242477","volume":"52","author":"CP Chen","year":"2013","unstructured":"Chen, C.P., Li, H., Wei, Y., Xia, T., Tang, Y.Y.: A local contrast method for small infrared target detection. IEEE Trans. Geosci. Remote Sens. 52(1), 574\u2013581 (2013)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"3","key":"28_CR9","first-page":"452","volume":"13","author":"J Han","year":"2016","unstructured":"Han, J., Ma, Y., Huang, J., Mei, X., Ma, J.: An infrared small target detecting algorithm based on human visual system. IEEE Geosci. Remote Sens. Lett. 13(3), 452\u2013456 (2016)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"9","key":"28_CR10","doi-asserted-by":"publisher","first-page":"7104","DOI":"10.1109\/TGRS.2019.2911513","volume":"57","author":"Y Qin","year":"2019","unstructured":"Qin, Y., Bruzzone, L., Gao, C., Li, B.: Infrared small target detection based on facet kernel and random walker. IEEE Trans. Geosci. Remote Sens. 57(9), 7104\u20137118 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"28_CR11","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":"28_CR12","doi-asserted-by":"crossref","unstructured":"Pang, D., Shan, T., Ma, Y., Ma, P., Hu, T., Tao, R.: LRTA-SP: Low rank tensor approximation with saliency prior for small target detection in infrared videos. IEEE Trans. Aerosp. Electron. Syst. (2024)","DOI":"10.1109\/TAES.2024.3474652"},{"key":"28_CR13","doi-asserted-by":"crossref","unstructured":"Liu, M., Du, H.y., Zhao, Y.j., Dong, L.q., Hui, M., Wang, S.: Image small target detection based on deep learning with snr controlled sample generation. Curr. Trends Comput. Sci. Mech. Autom. 1(211-220), 1\u20132 (2017)","DOI":"10.1515\/9783110584974-025"},{"key":"28_CR14","first-page":"1","volume":"61","author":"H Sun","year":"2023","unstructured":"Sun, H., Bai, J., Yang, F., Bai, X.: Receptive-field and direction induced attention network for infrared dim small target detection with a large-scale dataset irdst. IEEE Trans. Geosci. Remote Sens. 61, 1\u201313 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"11","key":"28_CR15","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., Barnard, K.: 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":"28_CR16","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1109\/TIP.2022.3228497","volume":"32","author":"X Wu","year":"2022","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 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"28_CR17","doi-asserted-by":"publisher","first-page":"1745","DOI":"10.1109\/TIP.2022.3199107","volume":"32","author":"B Li","year":"2022","unstructured":"Li, B., Xiao, C., Wang, L., Wang, Y., Lin, Z., Li, M., An, W., Guo, Y.: Dense nested attention network for infrared small target detection. IEEE Trans. Image Process. 32, 1745\u20131758 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Ma, Y., Fan, F., Huang, J., Wu, K., Wang, G.: Towards accurate infrared small target detection via edge-aware gated transformer. IEEE J. Select. Topics Appl. Earth Observ. Remote Sens. (2024)","DOI":"10.1109\/JSTARS.2024.3386899"},{"key":"28_CR19","doi-asserted-by":"crossref","unstructured":"Guo, T., Zhou, B., Luo, F., Zhang, L., Gao, X.: DMFNet: dual-encoder multi-stage feature fusion network for infrared small target detection. IEEE Trans. Geosci. Remote Sens. 62, 1\u20134 (2024)","DOI":"10.1109\/TGRS.2024.3376382"},{"issue":"1","key":"28_CR20","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1186\/s40537-023-00876-4","volume":"11","author":"B Khemani","year":"2024","unstructured":"Khemani, B., Patil, S., Kotecha, K., Tanwar, S.: A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions. J. Big Data 11(1), 18 (2024)","journal-title":"J. Big Data"},{"issue":"4","key":"28_CR21","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1109\/MSP.2023.3262906","volume":"40","author":"G Leus","year":"2023","unstructured":"Leus, G., Marques, A.G., Moura, J.M., Ortega, A., Shuman, D.I.: Graph signal processing: history, development, impact, and outlook. IEEE Signal Process. Mag. 40(4), 49\u201360 (2023)","journal-title":"IEEE Signal Process. Mag."},{"key":"28_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128949","volume":"616","author":"Y Shen","year":"2025","unstructured":"Shen, Y., Li, Q., Xu, C., Chang, C., Yin, Q.: Graph-based context learning network for infrared small target detection. Neurocomputing 616, 128949 (2025)","journal-title":"Neurocomputing"},{"key":"28_CR23","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1109\/LSP.2019.2956367","volume":"27","author":"Y Huang","year":"2019","unstructured":"Huang, Y., Tang, Z., Chen, D., Su, K., Chen, C.: Batching soft IoU for training semantic segmentation networks. IEEE Signal Process. Lett. 27, 66\u201370 (2019)","journal-title":"IEEE Signal Process. Lett."},{"key":"28_CR24","doi-asserted-by":"crossref","unstructured":"Dai, Y., Wu, Y., Zhou, F., Barnard, K.: Asymmetric contextual modulation for infrared small target detection. In: Proceedings of the IEEE\/CVF Winter Conference on Applications Of Computer Vision, pp. 950\u2013959 (2021)","DOI":"10.1109\/WACV48630.2021.00099"},{"key":"28_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhang, R., Yang, Y., Bai, H., Zhang, J., Guo, J.: ISNet: shape matters for infrared small target detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 877\u2013886 (2022)","DOI":"10.1109\/CVPR52688.2022.00095"}],"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\/978-981-95-5764-6_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T06:08:25Z","timestamp":1769148505000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5764-6_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557639","9789819557646"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5764-6_28","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":"24 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"}}]}}