{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T04:10:57Z","timestamp":1770523857929,"version":"3.49.0"},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100005046","name":"Natural Science Foundation of Heilongjiang Province","doi-asserted-by":"publisher","award":["LH2022F005"],"award-info":[{"award-number":["LH2022F005"]}],"id":[{"id":"10.13039\/501100005046","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s10489-025-06264-0","type":"journal-article","created":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T05:10:04Z","timestamp":1737349804000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Semantic-spatial guided context propagation network for camouflaged object detection"],"prefix":"10.1007","volume":"55","author":[{"given":"Junchao","family":"Ren","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bingbing","family":"Kang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxi","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanliang","family":"Ge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2442-330X","authenticated-orcid":false,"given":"Hongbo","family":"Bi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,20]]},"reference":[{"key":"6264_CR1","doi-asserted-by":"crossref","unstructured":"Fan DP, Ji GP, Zhou T, Chen G, Fu H, Shen J, Shao L (2020) Pranet: Parallel reverse attention network for polyp segmentation. In: International conference on medical image computing and computer-assisted intervention, Springer, pp 263\u2013273","DOI":"10.1007\/978-3-030-59725-2_26"},{"key":"6264_CR2","doi-asserted-by":"crossref","unstructured":"Xiao B, Hu J, Li W, Pun CM, Bi X (2024) Ctnet: Contrastive transformer network for polyp segmentation. IEEE Trans Cybern","DOI":"10.1109\/TCYB.2024.3368154"},{"key":"6264_CR3","doi-asserted-by":"crossref","unstructured":"Fan DP, Zhou T, Ji GP, Zhou Y, Chen G, Fu H, Shen J, Shao L (2020) Inf-net: Automatic covid-19 lung infection segmentation from ct images. IEEE Trans Med Imaging 39(8):2626\u20132637","DOI":"10.1109\/TMI.2020.2996645"},{"key":"6264_CR4","doi-asserted-by":"publisher","first-page":"3113","DOI":"10.1109\/TIP.2021.3058783","volume":"30","author":"YH Wu","year":"2021","unstructured":"Wu YH, Gao SH, Mei J, Xu J, Fan DP, Zhang RG, Cheng MM (2021) Jcs: An explainable covid-19 diagnosis system by joint classification and segmentation. IEEE Trans Image Process 30:3113\u20133126","journal-title":"IEEE Trans Image Process"},{"key":"6264_CR5","first-page":"1","volume":"70","author":"Y Bao","year":"2021","unstructured":"Bao Y, Song K, Liu J, Wang Y, Yan Y, Yu H, Li X (2021) Triplet-graph reasoning network for few-shot metal generic surface defect segmentation. IEEE Trans Instrum Meas 70:1\u201311","journal-title":"IEEE Trans Instrum Meas"},{"key":"6264_CR6","first-page":"1","volume":"71","author":"X Zhou","year":"2021","unstructured":"Zhou X, Fang H, Liu Z, Zheng B, Sun Y, Zhang J, Yan C (2021) Dense attention-guided cascaded network for salient object detection of strip steel surface defects. IEEE Trans Instrum Meas 71:1\u201314","journal-title":"IEEE Trans Instrum Meas"},{"key":"6264_CR7","doi-asserted-by":"crossref","unstructured":"Abdi A, Safabakhsh R (2022) An automatic graphic pattern generation algorithm and its application to the multipurpose camouflage pattern design. IEEE Trans Cybern","DOI":"10.1109\/TCYB.2022.3140394"},{"key":"6264_CR8","doi-asserted-by":"crossref","unstructured":"Liu M, Di X (2023) Extraordinary mhnet: military high-level camouflage object detection network and dataset. Neurocomput 549","DOI":"10.1016\/j.neucom.2023.126466"},{"issue":"10","key":"6264_CR9","doi-asserted-by":"publisher","first-page":"6981","DOI":"10.1109\/TCSVT.2022.3178173","volume":"32","author":"G Chen","year":"2022","unstructured":"Chen G, Liu SJ, Sun YJ, Ji GP, Wu YF, Zhou T (2022) Camouflaged object detection via context-aware cross-level fusion. IEEE Trans Circ Syst Video Technol 32(10):6981\u20136993","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"6264_CR10","doi-asserted-by":"crossref","unstructured":"Yan X, Sun M, Han Y, Wang Z (2023) Camouflaged object segmentation based on matching\u2013recognition\u2013refinement network. IEEE Trans Neural Netw Learn Syst","DOI":"10.1109\/TNNLS.2023.3291595"},{"key":"6264_CR11","doi-asserted-by":"crossref","unstructured":"Zhang Y, Zhang J, Hamidouche W, Deforges O (2023) Predictive uncertainty estimation for camouflaged object detection. IEEE Trans Image Process","DOI":"10.1109\/TIP.2023.3287137"},{"key":"6264_CR12","doi-asserted-by":"crossref","unstructured":"He C, Li K, Zhang Y, Tang L, Zhang Y, Guo Z, Li X (2023) Camouflaged object detection with feature decomposition and edge reconstruction. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 22046\u201322055","DOI":"10.1109\/CVPR52729.2023.02111"},{"key":"6264_CR13","doi-asserted-by":"crossref","unstructured":"Ge Y, Ren J, Zhang C, He M, Bi H, Zhang Q (2024) Feature-aware and iterative refinement network for camouflaged object detection. Vis Comput 1\u201318","DOI":"10.1007\/s00371-024-03688-6"},{"key":"6264_CR14","doi-asserted-by":"crossref","unstructured":"Ge Y, Zhong Y, Ren J, He M, Bi H, Zhang Q (2024) Camouflaged object detection via location-awareness and feature fusion. Image Vis Comput 105339","DOI":"10.1016\/j.imavis.2024.105339"},{"key":"6264_CR15","doi-asserted-by":"crossref","unstructured":"Ge Y, Liang T, Ren J, Chen J, Bi H (2024) Enhanced salient object detection in remote sensing images via dual-stream semantic interactive network. Vis Comput 1\u201317","DOI":"10.1007\/s00371-024-03713-8"},{"key":"6264_CR16","doi-asserted-by":"crossref","unstructured":"Fan DP, Ji GP, Sun G, Cheng MM, Shen J, Shao L (2020) Camouflaged object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 2777\u20132787","DOI":"10.1109\/CVPR42600.2020.00285"},{"key":"6264_CR17","doi-asserted-by":"crossref","unstructured":"Yang F, Zhai Q, Li X, Huang R, Luo A, Cheng H, Fan DP (2021) Uncertainty-guided transformer reasoning for camouflaged object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 4146\u20134155","DOI":"10.1109\/ICCV48922.2021.00411"},{"key":"6264_CR18","doi-asserted-by":"crossref","unstructured":"Zhou X, Wu Z, Cong R (2024) Decoupling and integration network for camouflaged object detection. IEEE Trans Multimed","DOI":"10.1109\/TMM.2024.3360710"},{"key":"6264_CR19","doi-asserted-by":"crossref","unstructured":"Yin B, Zhang X, Fan DP, Jiao S, Cheng MM, Van\u00a0Gool L, Hou Q (2024) Camoformer: Masked separable attention for camouflaged object detection. IEEE Trans Pattern Anal Mach Intell","DOI":"10.1109\/TPAMI.2024.3438565"},{"key":"6264_CR20","doi-asserted-by":"crossref","unstructured":"Yao S, Sun H, Xiang TZ, Wang X, Cao X (2024) Hierarchical graph interaction transformer with dynamic token clustering for camouflaged object detection. IEEE Trans Image Process","DOI":"10.1109\/TIP.2024.3475219"},{"key":"6264_CR21","doi-asserted-by":"crossref","unstructured":"Luo Z, Liu N, Zhao W, Yang X, Zhang D, Fan DP, Khan F, Han J (2024) Vscode: General visual salient and camouflaged object detection with 2d prompt learning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 17169\u201317180","DOI":"10.1109\/CVPR52733.2024.01625"},{"key":"6264_CR22","doi-asserted-by":"crossref","unstructured":"Pang Y, Zhao X, Xiang TZ, Zhang L, Lu H (2024) Zoomnext: A unified collaborative pyramid network for camouflaged object detection. IEEE Trans Pattern Anal Mach Intell","DOI":"10.1109\/TPAMI.2024.3417329"},{"key":"6264_CR23","doi-asserted-by":"crossref","unstructured":"Bhajantri NU, Nagabhushan P (2006) Camouflage defect identification: a novel approach. In: 9th international conference on information technology (ICIT\u201906), IEEE, pp 145\u2013148","DOI":"10.1109\/ICIT.2006.34"},{"key":"6264_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12862-016-0854-2","volume":"17","author":"J Troscianko","year":"2017","unstructured":"Troscianko J, Skelhorn J, Stevens M (2017) Quantifying camouflage: how to predict detectability from appearance. BMC Evol Biol 17:1\u201313","journal-title":"BMC Evol Biol"},{"issue":"8","key":"6264_CR25","doi-asserted-by":"publisher","first-page":"1883","DOI":"10.1111\/2041-210X.13019","volume":"9","author":"TW Pike","year":"2018","unstructured":"Pike TW (2018) Quantifying camouflage and conspicuousness using visual salience. Methods Ecol Evol 9(8):1883\u20131895","journal-title":"Methods Ecol Evol"},{"key":"6264_CR26","doi-asserted-by":"crossref","unstructured":"Sengottuvelan P, Wahi A, Shanmugam A (2008) Performance of decamouflaging through exploratory image analysis. In: 2008 1st international conference on emerging trends in engineering and technology, IEEE, pp 6\u201310","DOI":"10.1109\/ICETET.2008.232"},{"key":"6264_CR27","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1016\/j.ieri.2013.11.050","volume":"4","author":"SK Singh","year":"2013","unstructured":"Singh SK, Dhawale CA, Misra S (2013) Survey of object detection methods in camouflaged image. Ieri Procedia 4:351\u2013357","journal-title":"Ieri Procedia"},{"key":"6264_CR28","doi-asserted-by":"crossref","unstructured":"Mei H, Ji GP, Wei Z, Yang X, Wei X, Fan DP (2021) Camouflaged object segmentation with distraction mining. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8772\u20138781","DOI":"10.1109\/CVPR46437.2021.00866"},{"key":"6264_CR29","doi-asserted-by":"crossref","unstructured":"Li A, Zhang J, Lv Y, Liu B, Zhang T, Dai Y (2021) Uncertainty-aware joint salient object and camouflaged object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10071\u201310081","DOI":"10.1109\/CVPR46437.2021.00994"},{"issue":"10","key":"6264_CR30","doi-asserted-by":"publisher","first-page":"6024","DOI":"10.1109\/TPAMI.2021.3085766","volume":"44","author":"DP Fan","year":"2021","unstructured":"Fan DP, Ji GP, Cheng MM, Shao L (2021) Concealed object detection. IEEE Trans Pattern Anal Mach Intell 44(10):6024\u20136042","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6264_CR31","doi-asserted-by":"crossref","unstructured":"Zhang M, Xu S, Piao Y, Shi D, Lin S, Lu H (2022) Preynet: Preying on camouflaged objects. In: Proceedings of the 30th ACM international conference on multimedia, pp 5323\u20135332","DOI":"10.1145\/3503161.3548178"},{"issue":"10","key":"6264_CR32","doi-asserted-by":"publisher","first-page":"4593","DOI":"10.1007\/s00371-022-02611-1","volume":"39","author":"Q Zhang","year":"2023","unstructured":"Zhang Q, Ge Y, Zhang C, Bi H (2023) Tprnet: camouflaged object detection via transformer-induced progressive refinement network. Vis Comput 39(10):4593\u20134607","journal-title":"Vis Comput"},{"issue":"21","key":"6264_CR33","doi-asserted-by":"publisher","first-page":"25216","DOI":"10.1007\/s10489-023-04898-6","volume":"53","author":"Y Deng","year":"2023","unstructured":"Deng Y, Ma J, Li Y, Zhang M, Wang L (2023) Ternary symmetric fusion network for camouflaged object detection. Appl Intell 53(21):25216\u201325231","journal-title":"Appl Intell"},{"issue":"19","key":"6264_CR34","doi-asserted-by":"publisher","first-page":"22429","DOI":"10.1007\/s10489-023-04645-x","volume":"53","author":"C Shi","year":"2023","unstructured":"Shi C, Ren B, Chen H, Zhao L, Lin C, Zhao Y (2023) Camouflaged object detection based on context-aware and boundary refinement. Appl Intell 53(19):22429\u201322445","journal-title":"Appl Intell"},{"key":"6264_CR35","doi-asserted-by":"crossref","unstructured":"Sun Y, Xu C, Yang J, Xuan H, Luo L (2025) Frequency-spatial entanglement learning for camouflaged object detection. In: european conference on computer vision, Springer, pp 343\u2013360","DOI":"10.1007\/978-3-031-72658-3_20"},{"key":"6264_CR36","doi-asserted-by":"crossref","unstructured":"Sun Y, Chen G, Zhou T, Zhang Y, Liu N (2021) Context-aware cross-level fusion network for camouflaged object detection. arXiv preprint arXiv:2105.12555","DOI":"10.24963\/ijcai.2021\/142"},{"key":"6264_CR37","doi-asserted-by":"crossref","unstructured":"Bi H, Wu R, Liu Z, Zhu H, Zhang C, Xiang TZ (2023) Cross-modal hierarchical interaction network for rgb-d salient object detection. Pattern Recognit 136","DOI":"10.1016\/j.patcog.2022.109194"},{"key":"6264_CR38","doi-asserted-by":"crossref","unstructured":"Ge Y, Zhang Q, Xiang TZ, Zhang C, Bi H (2022) Tcnet: Co-salient object detection via parallel interaction of transformers and cnns. IEEE Trans Circ Syst Video Technol","DOI":"10.1109\/TCSVT.2022.3225865"},{"key":"6264_CR39","doi-asserted-by":"crossref","unstructured":"Li X, Yang J, Li S, Lei J, Zhang J, Chen D (2023) Locate, refine and restore: A progressive enhancement network for camouflaged object detection. In: Proceedings of the 32nd international joint conference on artificial intelligence IJCAI, pp 1116\u20131124","DOI":"10.24963\/ijcai.2023\/124"},{"key":"6264_CR40","doi-asserted-by":"crossref","unstructured":"Zhang C, Bi H, Mo D, Sun W, Tong J, Jin W, Sun Y (2024) Ccnet: Collaborative camouflaged object detection via decoder-induced information interaction and supervision refinement network. Eng Appl Artif Intell 133","DOI":"10.1016\/j.engappai.2024.108328"},{"issue":"11","key":"6264_CR41","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254\u20131259","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6264_CR42","unstructured":"Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473"},{"key":"6264_CR43","doi-asserted-by":"crossref","unstructured":"Fu J, Liu J, Tian H, Li Y, Bao Y, Fang Z, Lu H (2019) Dual attention network for scene segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3146\u20133154","DOI":"10.1109\/CVPR.2019.00326"},{"key":"6264_CR44","doi-asserted-by":"crossref","unstructured":"Zhai Q, Li X, Yang F, Chen C, Cheng H, Fan DP (2021) Mutual graph learning for camouflaged object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12997\u201313007","DOI":"10.1109\/CVPR46437.2021.01280"},{"key":"6264_CR45","doi-asserted-by":"crossref","unstructured":"Pei J, Cheng T, Fan DP, Tang H, Chen C, Van\u00a0Gool L (2022) Osformer: one-stage camouflaged instance segmentation with transformers. In: european conference on computer vision, Springer, pp 19\u201337","DOI":"10.1007\/978-3-031-19797-0_2"},{"key":"6264_CR46","unstructured":"He C, Li K, Zhang Y, Zhang Y, Guo Z, Li X, Danelljan M, Yu F (2023) Strategic preys make acute predators: Enhancing camouflaged object detectors by generating camouflaged objects. arXiv preprint arXiv:2308.03166"},{"key":"6264_CR47","doi-asserted-by":"crossref","unstructured":"Li C, Jiao G, Yue G, He R, Huang J (2024) Multi-scale pooling learning for camouflaged instance segmentation. Appl Intell pp 1\u201315","DOI":"10.1007\/s10489-024-05369-2"},{"key":"6264_CR48","unstructured":"Tan M, Le Q (2019) Efficientnet: Rethinking model scaling for convolutional neural networks. In: International conference on machine learning, PMLR, pp 6105\u20136114"},{"key":"6264_CR49","unstructured":"Zhang H, Goodfellow I, Metaxas D, Odena A (2019) Self-attention generative adversarial networks. In: International conference on machine learning, PMLR, pp 7354\u20137363"},{"key":"6264_CR50","unstructured":"Lee CY, Xie S, Gallagher P, Zhang Z, Tu Z (2015) Deeply-supervised nets. In: Artificial intelligence and statistics, PMLR, pp 562\u2013570"},{"key":"6264_CR51","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s10479-005-5724-z","volume":"134","author":"PT De Boer","year":"2005","unstructured":"De Boer PT, Kroese DP, Mannor S, Rubinstein RY (2005) A tutorial on the cross-entropy method. Ann Oper Res 134:19\u201367","journal-title":"Ann Oper Res"},{"key":"6264_CR52","doi-asserted-by":"crossref","unstructured":"M\u00e1ttyus G, Luo W, Urtasun R (2017) Deeproadmapper: Extracting road topology from aerial images. In: Proceedings of the IEEE international conference on computer vision, pp 3438\u20133446","DOI":"10.1109\/ICCV.2017.372"},{"key":"6264_CR53","unstructured":"Paszke A, Gross S, Massa F, Lerer A, Bradbury J, Chanan G, Killeen T, Lin Z, Gimelshein N, Antiga L et\u00a0al (2019) Pytorch: An imperative style, high-performance deep learning library. Adv Neural Inf Process Syst 32"},{"key":"6264_CR54","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"6264_CR55","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.cviu.2019.04.006","volume":"184","author":"TN Le","year":"2019","unstructured":"Le TN, Nguyen TV, Nie Z, Tran MT, Sugimoto A (2019) Anabranch network for camouflaged object segmentation. Comp Vision Image Underst 184:45\u201356","journal-title":"Comp Vision Image Underst"},{"key":"6264_CR56","doi-asserted-by":"crossref","unstructured":"Lv Y, Zhang J, Dai Y, Li A, Liu B, Barnes N, Fan DP (2021) Simultaneously localize, segment and rank the camouflaged objects. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 11591\u201311601","DOI":"10.1109\/CVPR46437.2021.01142"},{"key":"6264_CR57","doi-asserted-by":"crossref","unstructured":"Fan DP, Cheng MM, Liu Y, Li T, Borji A (2017) Structure-measure: A new way to evaluate foreground maps. In: Proceedings of the IEEE international conference on computer vision, pp 4548\u20134557","DOI":"10.1109\/ICCV.2017.487"},{"key":"6264_CR58","doi-asserted-by":"crossref","unstructured":"Perazzi F, Kr\u00e4henb\u00fchl P, Pritch YHornung A (2012) Saliency filters: Contrast based filtering for salient region detection. In: 2012 IEEE conference on computer vision and pattern recognition, IEEE, pp 733\u2013740","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"6264_CR59","doi-asserted-by":"crossref","unstructured":"Fan DP, Gong C, Cao Y, Ren B, Cheng MM, Borji A (2018) Enhanced-alignment measure for binary foreground map evaluation. arXiv preprint arXiv:1805.10421","DOI":"10.24963\/ijcai.2018\/97"},{"key":"6264_CR60","doi-asserted-by":"crossref","unstructured":"Achanta R, Hemami S, Estrada F, Susstrunk S (2009) Frequency-tuned salient region detection. In: 2009 IEEE conference on computer vision and pattern recognition, IEEE, pp 1597\u20131604","DOI":"10.1109\/CVPR.2009.5206596"},{"key":"6264_CR61","doi-asserted-by":"crossref","unstructured":"Ji GP, Zhu L, Zhuge M, Fu K (2022) Fast camouflaged object detection via edge-based reversible re-calibration network. Pattern Recognit 123","DOI":"10.1016\/j.patcog.2021.108414"},{"issue":"10","key":"6264_CR62","doi-asserted-by":"publisher","first-page":"6024","DOI":"10.1109\/TPAMI.2021.3085766","volume":"44","author":"DP Fan","year":"2022","unstructured":"Fan DP, Ji GP, Cheng MM, Shao L (2022) Concealed object detection. IEEE Trans Pattern Anal Mach Intell 44(10):6024\u20136042","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6264_CR63","doi-asserted-by":"crossref","unstructured":"Zhu H, Li P, Xie H, Yan X, Liang D, Chen D, Wei M, Qin J (2022) I can find you! boundary-guided separated attention network for camouflaged object detection. In: Proceedings of the AAAI conference on artificial intelligence, vol 36, pp 3608\u20133616","DOI":"10.1609\/aaai.v36i3.20273"},{"key":"6264_CR64","doi-asserted-by":"publisher","first-page":"7036","DOI":"10.1109\/TIP.2022.3217695","volume":"31","author":"T Zhou","year":"2022","unstructured":"Zhou T, Zhou Y, Gong C, Yang J, Zhang Y (2022) Feature aggregation and propagation network for camouflaged object detection. IEEE Trans Image Process 31:7036\u20137047","journal-title":"IEEE Trans Image Process"},{"key":"6264_CR65","doi-asserted-by":"crossref","unstructured":"Chen T, Xiao J, Hu X, Zhang G, Wang S (2022) Boundary-guided network for camouflaged object detection. Knowl-Based Syst 248","DOI":"10.1016\/j.knosys.2022.108901"},{"key":"6264_CR66","doi-asserted-by":"crossref","unstructured":"He R, Dong Q, Lin J, Lau RW (2023) Weakly-supervised camouflaged object detection with scribble annotations. In: Proceedings of the AAAI conference on artificial intelligence, vol 37, pp 781\u2013789","DOI":"10.1609\/aaai.v37i1.25156"},{"issue":"1","key":"6264_CR67","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1007\/s11633-022-1365-9","volume":"20","author":"GP Ji","year":"2023","unstructured":"Ji GP, Fan DP, Chou YC, Dai D, Liniger A, Van Gool L (2023) Deep gradient learning for efficient camouflaged object detection. Mach Intell Res 20(1):92\u2013108","journal-title":"Mach Intell Res"},{"key":"6264_CR68","doi-asserted-by":"crossref","unstructured":"Ge Y, Ren J, Zhang Q, He M, Bi H, Zhang C (2024) Camouflaged object detection via cross-level refinement and interaction network. Image Vis Comput 144","DOI":"10.1016\/j.imavis.2024.104973"},{"key":"6264_CR69","unstructured":"Chen LC, Papandreou G, Schroff F, Adam H (2017) Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587"},{"key":"6264_CR70","doi-asserted-by":"crossref","unstructured":"Liu S, Huang D et\u00a0al (2018) Receptive field block net for accurate and fast object detection. In: Proceedings of the European conference on computer vision (ECCV), pp 385\u2013400","DOI":"10.1007\/978-3-030-01252-6_24"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06264-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-025-06264-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06264-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T17:22:16Z","timestamp":1740244936000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-025-06264-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,20]]},"references-count":70,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["6264"],"URL":"https:\/\/doi.org\/10.1007\/s10489-025-06264-0","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,20]]},"assertion":[{"value":"4 January 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2025","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 declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interest"}}],"article-number":"349"}}