{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T15:32:51Z","timestamp":1786980771799,"version":"3.56.0"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T00:00:00Z","timestamp":1674604800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T00:00:00Z","timestamp":1674604800000},"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":["Appl Intell"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s10489-022-04421-3","type":"journal-article","created":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T06:03:21Z","timestamp":1674626601000},"page":"18219-18238","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Multi-scale attention context-aware network for detection and localization of image splicing"],"prefix":"10.1007","volume":"53","author":[{"given":"Ruyong","family":"Ren","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaozhang","family":"Niu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junfeng","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojie","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,1,25]]},"reference":[{"key":"4421_CR1","doi-asserted-by":"publisher","first-page":"300","DOI":"10.5201\/ipol.2016.163","volume":"6","author":"JMD Martino","year":"2016","unstructured":"Martino JMD, Facciolo G, Meinhardt-Llopis E (2016) Poisson image editing. Image Process Line 6:300\u2013325. https:\/\/doi.org\/10.5201\/ipol.2016.163","journal-title":"Image Process Line"},{"key":"4421_CR2","doi-asserted-by":"publisher","unstructured":"Hao J, Zhang Z, Yang S, Xie D, Pu S (2021) Transforensics: Image forgery localization with dense self-attention. In: 2021 IEEE\/CVF international conference on computer vision, ICCV 2021. IEEE, Montreal, 10-17 October, 2021, pp 15035\u201315044. https:\/\/doi.org\/10.1109\/ICCV48922.2021.01478","DOI":"10.1109\/ICCV48922.2021.01478"},{"key":"4421_CR3","doi-asserted-by":"publisher","unstructured":"Bappy JH, Roy-Chowdhury AK, Bunk J, Nataraj L, Manjunath BS (2017) Exploiting spatial structure for localizing manipulated image regions. In: IEEE international conference on computer vision, ICCV 2017. IEEE computer society, Italy, 22-29 October, 2017, pp 4980\u20134989. https:\/\/doi.org\/10.1109\/ICCV.2017.532","DOI":"10.1109\/ICCV.2017.532"},{"issue":"7","key":"4421_CR4","doi-asserted-by":"publisher","first-page":"3286","DOI":"10.1109\/TIP.2019.2895466","volume":"28","author":"JH Bappy","year":"2019","unstructured":"Bappy JH, Simons C, Nataraj L, Manjunath BS, Roy-Chowdhury AK (2019) Hybrid LSTM and encoder-decoder architecture for detection of image forgeries. IEEE Trans Image Process 28(7):3286\u20133300. https:\/\/doi.org\/10.1109\/TIP.2019.2895466","journal-title":"IEEE Trans Image Process"},{"key":"4421_CR5","doi-asserted-by":"publisher","unstructured":"Wu Y, AbdAlmageed W, Natarajan P (2019) Mantra-net: manipulation tracing network for detection and localization of image forgeries with anomalous features. In: IEEE conference on computer vision and pattern recognition, CVPR 2019. Computer Vision Foundation \/ IEEE, USA, 16-20 June, 2019, pp 9543\u20139552. https:\/\/doi.org\/10.1109\/CVPR.2019.00977","DOI":"10.1109\/CVPR.2019.00977"},{"key":"4421_CR6","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.ins.2019.09.038","volume":"511","author":"B Xiao","year":"2020","unstructured":"Xiao B, Wei Y, Bi X, Li W, Ma J (2020) Image splicing forgery detection combining coarse to refined convolutional neural network and adaptive clustering. Inf Sci 511:172\u2013191. https:\/\/doi.org\/10.1016\/j.ins.2019.09.038","journal-title":"Inf Sci"},{"key":"4421_CR7","doi-asserted-by":"publisher","unstructured":"Bi X, Wei Y, Xiao B, Li W (2019) Rru-net: the ringed residual u-net for image splicing forgery detection. In: IEEE conference on computer vision and pattern recognition workshops, CVPR workshops 2019. Computer Vision Foundation \/ IEEE, long beach, CA, USA, 16-20 June, 2019, pp 30\u201339. https:\/\/doi.org\/10.1109\/CVPRW.2019.00010","DOI":"10.1109\/CVPRW.2019.00010"},{"key":"4421_CR8","doi-asserted-by":"publisher","unstructured":"Huh M, Liu A, Owens A, Efros AA (2018) Fighting fake news: image splice detection via learned self-consistency. In: ferrari V, Hebert M, Sminchisescu C, Weiss Y (eds) Computer vision - ECCV 2018 - 15th European conference, Germany, 8-14 September, 2018, Proceedings, Part XI, Lecture Notes in Computer Science. Springer, vol 11215, pp 106\u2013124. https:\/\/doi.org\/10.1007\/978-3-030-01252-6_7","DOI":"10.1007\/978-3-030-01252-6_7"},{"key":"4421_CR9","doi-asserted-by":"publisher","unstructured":"Bi X, Zhang Z, Xiao B (2021) Reality transform adversarial generators for image splicing forgery detection and localization. In: 2021 IEEE\/CVF international conference on computer vision, ICCV 2021. IEEE, Canada, 10-17 October, 2021, pp 14274\u201314283. https:\/\/doi.org\/10.1109\/ICCV48922.2021.01403","DOI":"10.1109\/ICCV48922.2021.01403"},{"key":"4421_CR10","doi-asserted-by":"publisher","unstructured":"Cozzolino D, Gragnaniello D, Verdoliva L (2014) Image forgery localization through the fusion of camera-based, feature-based and pixel-based techniques. In: 2014 IEEE international conference on image processing, ICIP 2014. IEEE, France, 27-30 October, 2014, pp 5302\u20135306. https:\/\/doi.org\/10.1109\/ICIP.2014.7026073","DOI":"10.1109\/ICIP.2014.7026073"},{"issue":"5","key":"4421_CR11","doi-asserted-by":"publisher","first-page":"1566","DOI":"10.1109\/TIFS.2012.2202227","volume":"7","author":"P Ferrara","year":"2012","unstructured":"Ferrara P, Bianchi T, Rosa AD, Piva A (2012) Image forgery localization via fine-grained analysis of CFA artifacts. IEEE Trans Inf Forensics Secur 7(5):1566\u20131577. https:\/\/doi.org\/10.1109\/TIFS.2012.2202227","journal-title":"IEEE Trans Inf Forensics Secur"},{"issue":"7","key":"4421_CR12","doi-asserted-by":"publisher","first-page":"1182","DOI":"10.1109\/TIFS.2013.2265677","volume":"8","author":"TJ de Carvalho","year":"2013","unstructured":"de Carvalho TJ, Riess C, Angelopoulou E, Pedrini H, de Rezende Rocha A (2013) Exposing digital image forgeries by illumination color classification. IEEE Trans Inf Forensics Secur 8(7):1182\u20131194. https:\/\/doi.org\/10.1109\/TIFS.2013.2265677","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"4421_CR13","doi-asserted-by":"publisher","unstructured":"Riess C, Angelopoulou E (2010) Scene illumination as an indicator of image manipulation. In: B\u00f6hme R, Fong PWL, Safavi-Naini R (eds) Information hiding - 12th international conference, IH 2010. Springer, Canada, 28-30 June, 2010, Revised selected papers, lecture notes in computer science, vol 6387, pp 66\u201380. https:\/\/doi.org\/10.1007\/978-3-642-16435-4_6","DOI":"10.1007\/978-3-642-16435-4_6"},{"key":"4421_CR14","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.jvcir.2017.09.003","volume":"49","author":"M Barni","year":"2017","unstructured":"Barni M, Bondi L, Bonettini N, Bestagini P, Costanzo A, Maggini M, Tondi B, Tubaro S (2017) Aligned and non-aligned double JPEG detection using convolutional neural networks. J Vis Commun Image Represent 49:153\u2013163. https:\/\/doi.org\/10.1016\/j.jvcir.2017.09.003","journal-title":"J Vis Commun Image Represent"},{"key":"4421_CR15","doi-asserted-by":"publisher","unstructured":"Bianchi T, Rosa AD, Piva A (2011) Improved DCT coefficient analysis for forgery localization in JPEG images. In: Proceedings of the IEEE international conference on acoustics, speech, and signal processing, ICASSP 2011, Prague Congress Center, Prague, Czech Republic. IEEE, 22-27 May, 2011, pp 2444\u20132447. https:\/\/doi.org\/10.1109\/ICASSP.2011.5946978","DOI":"10.1109\/ICASSP.2011.5946978"},{"issue":"7","key":"4421_CR16","doi-asserted-by":"publisher","first-page":"3286","DOI":"10.1109\/TIP.2019.2895466","volume":"28","author":"JH Bappy","year":"2019","unstructured":"Bappy JH, Simons C, Nataraj L, Manjunath BS, Roy-Chowdhury AK (2019) Hybrid LSTM and encoder-decoder architecture for detection of image forgeries. IEEE Trans Image Process 28(7):3286\u20133300. https:\/\/doi.org\/10.1109\/TIP.2019.2895466","journal-title":"IEEE Trans Image Process"},{"key":"4421_CR17","doi-asserted-by":"publisher","unstructured":"Zhou P, Han X, Morariu VI, Davis LS (2017) Two-stream neural networks for tampered face detection. In: 2017 IEEE conference on computer vision and pattern recognition workshops, CVPR workshops 2017, honolulu, HI, USA, 21-26 July, 2017, pp 1831\u20131839. IEEE Computer Society. https:\/\/doi.org\/10.1109\/CVPRW.2017.229","DOI":"10.1109\/CVPRW.2017.229"},{"key":"4421_CR18","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.ins.2019.09.038","volume":"511","author":"B Xiao","year":"2020","unstructured":"Xiao B, Wei Y, Bi X, Li W, Ma J (2020) Image splicing forgery detection combining coarse to refined convolutional neural network and adaptive clustering. Inf Sci 511:172\u2013191. https:\/\/doi.org\/10.1016\/j.ins.2019.09.038","journal-title":"Inf Sci"},{"key":"4421_CR19","doi-asserted-by":"publisher","unstructured":"Islam A, Long C, Basharat A, Hoogs A (2020) DOA-GAN: dual-order attentive generative adversarial network for image copy-move forgery detection and localization. In: 2020 IEEE\/CVF conference on computer vision and pattern recognition, CVPR 2020. Computer Vision Foundation \/ IEEE, Seattle, WA, USA, 13-19 June, 2020, pp 4675\u20134684. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00473","DOI":"10.1109\/CVPR42600.2020.00473"},{"key":"4421_CR20","doi-asserted-by":"publisher","unstructured":"Zhou P, Han X, Morariu VI, Davis LS (2017) Two-stream neural networks for tampered face detection. In: 2017 IEEE conference on computer vision and pattern recognition workshops, CVPR workshops 2017. IEEE Computer Society, Honolulu, HI, USA, 21-26 July, 2017, pp 1831\u20131839. https:\/\/doi.org\/10.1109\/CVPRW.2017.229","DOI":"10.1109\/CVPRW.2017.229"},{"key":"4421_CR21","doi-asserted-by":"publisher","unstructured":"Amerini I, Uricchio T, Ballan L, Caldelli R (2017) Localization of JPEG double compression through multi-domain convolutional neural networks. In: 2017 IEEE conference on computer vision and pattern recognition workshops, CVPR workshops 2017. IEEE Computer Society, USA, 21-26 July, 2017, pp 1865\u20131871. https:\/\/doi.org\/10.1109\/CVPRW.2017.233","DOI":"10.1109\/CVPRW.2017.233"},{"key":"4421_CR22","doi-asserted-by":"publisher","unstructured":"Bappy JH, Roy-Chowdhury AK, Bunk J, Nataraj L, Manjunath BS (2017) Exploiting spatial structure for localizing manipulated image regions. In: IEEE international conference on computer vision, ICCV 2017. IEEE computer society, Italy, 22-29 October, 2017, pp 4980\u20134989. https:\/\/doi.org\/10.1109\/ICCV.2017.532","DOI":"10.1109\/ICCV.2017.532"},{"key":"4421_CR23","doi-asserted-by":"publisher","unstructured":"Carion N, Massa F, Synnaeve G, Usunier N, Kirillov A, Zagoruyko S (2020) End-to-end object detection with transformers. In: Vedaldi A, Bischof H, Brox T, Frahm J (eds) Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, 23-28 August, 2020, Proceedings, Part I, lecture notes in computer science. Springer, vol 12346, pp 213\u2013229. https:\/\/doi.org\/10.1007\/978-3-030-58452-8_13","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"4421_CR24","unstructured":"Vaswani A, Ramachandran P, Srinivas A, Parmar N, Hechtman BA, Shlens J (2103) Scaling local self-attention for parameter efficient visual backbones. arXiv:2103.12731"},{"key":"4421_CR25","doi-asserted-by":"crossref","unstructured":"Vaswani A, Ramachandran P, Srinivas A, Parmar N, Hechtman BA, Shlens J (2021) Scaling local self-attention for parameter efficient visual backbones. arXiv:2103.12731","DOI":"10.1109\/CVPR46437.2021.01270"},{"key":"4421_CR26","doi-asserted-by":"publisher","unstructured":"Ye L, Rochan M, Liu Z, Wang Y (2019) Cross-modal self-attention network for referring image segmentation. In: IEEE conference on computer vision and pattern recognition, CVPR 2019. Computer Vision Foundation \/ IEEE, USA, 16-20 June, 2019, pp 10502\u201310511. https:\/\/doi.org\/10.1109\/CVPR.2019.01075","DOI":"10.1109\/CVPR.2019.01075"},{"key":"4421_CR27","doi-asserted-by":"crossref","unstructured":"Zheng S, Lu J, Zhao H, Zhu X, Luo Z, Wang Y, Fu Y, Feng J, Xiang T, Torr PHS, Zhang L (2020) Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers. arXiv:2012.15840","DOI":"10.1109\/CVPR46437.2021.00681"},{"key":"4421_CR28","doi-asserted-by":"publisher","unstructured":"Hu X, Zhang Z, Jiang Z, Chaudhuri S, Yang Z, Nevatia R (2020) SPAN: spatial pyramid attention network for image manipulation localization. In: Vedaldi A, Bischof H, Brox T, Frahm J (eds) Computer Vision - ECCV 2020 - 16th European conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXI, Lecture Notes in Computer Science, vol 12366, pp 312\u2013328. Springer. https:\/\/doi.org\/10.1007\/978-3-030-58589-1_19","DOI":"10.1007\/978-3-030-58589-1_19"},{"key":"4421_CR29","doi-asserted-by":"publisher","unstructured":"Islam A, Long C, Basharat A, Hoogs A (2020) DOA-GAN: dual-order attentive generative adversarial network for image copy-move forgery detection and localization. In: 2020 IEEE\/CVF conference on computer vision and pattern recognition, CVPR 2020, Seattle, WA, USA, June 13-19, 2020, pp 4675\u20134684. Computer Vision Foundation \/ IEEE. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00473","DOI":"10.1109\/CVPR42600.2020.00473"},{"key":"4421_CR30","doi-asserted-by":"publisher","first-page":"1280","DOI":"10.1109\/TASLP.2021.3053400","volume":"29","author":"L Qin","year":"2021","unstructured":"Qin L, Che W, Ni M, Li Y, Liu T (2021) Knowing where to leverage: context-aware graph convolutional network with an adaptive fusion layer for contextual spoken language understanding. IEEE ACM Trans Audio Speech Lang Process 29:1280\u20131289. https:\/\/doi.org\/10.1109\/TASLP.2021.3053400","journal-title":"IEEE ACM Trans Audio Speech Lang Process"},{"key":"4421_CR31","doi-asserted-by":"publisher","unstructured":"Zhao H, Shi J, Qi X, Wang X, Jia J (2017) Pyramid scene parsing network. In: 2017 IEEE conference on computer vision and pattern recognition, CVPR 2017, USA, July 21-26, 2017, pp 6230\u20136239. IEEE Computer Society. https:\/\/doi.org\/10.1109\/CVPR.2017.660","DOI":"10.1109\/CVPR.2017.660"},{"issue":"4","key":"4421_CR32","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"L Chen","year":"2018","unstructured":"Chen L, Papandreou G, Kokkinos I, Murphy K, Yuille AL (2018) Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans Pattern Anal Mach Intell 40(4):834\u2013848. https:\/\/doi.org\/10.1109\/TPAMI.2017.2699184","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4421_CR33","doi-asserted-by":"publisher","unstructured":"Fu J, Liu J, Tian H, Li Y, Bao Y, Fang Z, Lu H (2019) Dual attention network for scene segmentation. In: IEEE conference on computer vision and pattern recognition, CVPR 2019. Computer Vision Foundation \/ IEEE, USA, June 16-20, 2019, pp 3146\u20133154. https:\/\/doi.org\/10.1109\/CVPR.2019.00326","DOI":"10.1109\/CVPR.2019.00326"},{"key":"4421_CR34","doi-asserted-by":"publisher","unstructured":"Huang Z, Wang X, Huang L, Huang C, Wei Y, Liu W (2019) Ccnet: Criss-cross attention for semantic segmentation. In: 2019 IEEE\/CVF international conference on computer vision, ICCV 2019. IEEE, Seoul, Korea (South), October 27 - November 2, 2019, pp 603\u2013612. https:\/\/doi.org\/10.1109\/ICCV.2019.00069","DOI":"10.1109\/ICCV.2019.00069"},{"key":"4421_CR35","doi-asserted-by":"publisher","unstructured":"Zhang L, Dai J, Lu H, He Y, Wang G (2018) A bi-directional message passing model for salient object detection. In: 2018 IEEE conference on computer vision and pattern recognition, CVPR 2018. Computer Vision Foundation \/ IEEE Computer Society, USA, June 18-22, 2018, pp 1741\u20131750. https:\/\/doi.org\/10.1109\/CVPR.2018.00187","DOI":"10.1109\/CVPR.2018.00187"},{"key":"4421_CR36","doi-asserted-by":"publisher","unstructured":"Tan J, Xiong P, Lv Z, Xiao K, He Y (2020) Local context attention for salient object segmentation. In: Ishikawa H, Liu C, Pajdla T, Shi J (eds) Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part I, Lecture Notes in Computer Science, vol. 12622, pp 706\u2013722. Springer. https:\/\/doi.org\/10.1007\/978-3-030-69525-5_42","DOI":"10.1007\/978-3-030-69525-5_42"},{"key":"4421_CR37","doi-asserted-by":"crossref","unstructured":"Chen Z, Xu Q, Cong R, Huang Q (2020) Global context-aware progressive aggregation network for salient object detection. arXiv:2003.00651","DOI":"10.1609\/aaai.v34i07.6633"},{"key":"4421_CR38","doi-asserted-by":"publisher","unstructured":"Liu J, Hou Q, Cheng M, Feng J, Jiang J (2019) A simple pooling-based design for real-time salient object detection. In: IEEE conference on computer vision and pattern recognition, CVPR 2019, USA, June 16-20, 2019, pp 3917\u20133926. Computer Vision Foundation \/ IEEE. https:\/\/doi.org\/10.1109\/CVPR.2019.00404","DOI":"10.1109\/CVPR.2019.00404"},{"key":"4421_CR39","doi-asserted-by":"publisher","unstructured":"Dong J, Wang W, Tan T (2013) CASIA Image tampering detection evaluation database. In: 2013 IEEE China summit and international conference on signal and information processing, chinaSIP 2013, China, July 6-10, 2013, pp 422\u2013426. IEEE. https:\/\/doi.org\/10.1109\/ChinaSIP.2013.6625374","DOI":"10.1109\/ChinaSIP.2013.6625374"},{"key":"4421_CR40","doi-asserted-by":"crossref","unstructured":"Novozamsky A, Mahdian B, Saic S (2020) Imd2020: a large-scale annotated dataset tailored for detecting manipulated images. In: 2020 IEEE winter applications of computer vision workshops (WACVW), pp 71\u201380","DOI":"10.1109\/WACVW50321.2020.9096940"},{"key":"4421_CR41","doi-asserted-by":"publisher","unstructured":"Novoz\u00e1msk\u00fd A, Mahdian B, Saic S (2020) IMD2020: A large-scale annotated dataset tailored for detecting manipulated images. In: IEEE winter applications of computer vision workshops, WACV workshops 2020, USA, March 1-5, 2020, pp 71\u201380.IEEE. https:\/\/doi.org\/10.1109\/WACVW50321.2020.9096940","DOI":"10.1109\/WACVW50321.2020.9096940"},{"key":"4421_CR42","doi-asserted-by":"publisher","unstructured":"Hsu Y, Chang S (2006) Detecting image splicing using geometry invariants and camera characteristics consistency. In: Proceedings of the 2006 IEEE international conference on multimedia and expo, ICME 2006, July 9-12 2006, Canada, pp 549\u2013552. IEEE Computer Society. https:\/\/doi.org\/10.1109\/ICME.2006.262447","DOI":"10.1109\/ICME.2006.262447"},{"key":"4421_CR43","doi-asserted-by":"publisher","unstructured":"Guan H, Kozak M, Robertson E, Lee Y, Yates AN, Delgado A, Zhou D, Kheyrkhah T, Smith J, Fiscus JG (2019) MFC Datasets: large-scale benchmark datasets for media forensic challenge evaluation. In: IEEE winter applications of computer vision workshops, WACV workshops 2019, USA, January 7-11, 2019, pp 63\u201372. IEEE. https:\/\/doi.org\/10.1109\/WACVW.2019.00018","DOI":"10.1109\/WACVW.2019.00018"},{"key":"4421_CR44","doi-asserted-by":"publisher","unstructured":"Wang L, Lu H, Wang Y, Feng M, Wang D, Yin B, Ruan X (2017) Learning to detect salient objects with image-level supervision. In: 2017 IEEE conference on computer vision and pattern recognition, CVPR 2017, USA, July 21-26, 2017, pp 3796\u20133805. IEEE Computer Society. https:\/\/doi.org\/10.1109\/CVPR.2017.404","DOI":"10.1109\/CVPR.2017.404"},{"key":"4421_CR45","doi-asserted-by":"publisher","unstructured":"Dai Y, Gieseke F, Oehmcke S, Wu Y, Barnard K (2021) Attentional feature fusion. In: IEEE winter conference on applications of computer vision, WACV 2021, USA, January 3-8, 2021, pp 3559\u20133568. IEEE. https:\/\/doi.org\/10.1109\/WACV48630.2021.00360","DOI":"10.1109\/WACV48630.2021.00360"},{"key":"4421_CR46","doi-asserted-by":"publisher","unstructured":"Wu Z, Su L, Huang Q (2019) Cascaded partial decoder for fast and accurate salient object detection. In: IEEE conference on computer vision and pattern recognition, CVPR 2019, USA, June 16-20, 2019, pp 3907\u20133916. Computer Vision Foundation \/ IEEE. https:\/\/doi.org\/10.1109\/CVPR.2019.00403","DOI":"10.1109\/CVPR.2019.00403"},{"issue":"1","key":"4421_CR47","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s10479-005-5724-z","volume":"134","author":"P de Boer","year":"2005","unstructured":"de Boer P, Kroese DP, Mannor S, Rubinstein RY (2005) A tutorial on the cross-entropy method. Ann Oper Res 134(1):19\u201367. https:\/\/doi.org\/10.1007\/s10479-005-5724-z","journal-title":"Ann Oper Res"},{"key":"4421_CR48","doi-asserted-by":"publisher","unstructured":"M\u00e1ttyus G, Luo W, Urtasun R (2017) Deeproadmapper: extracting road topology from aerial images. In: IEEE international conference on computer vision, ICCV 2017, Italy, October 22-29, 2017, pp 3458\u20133466. IEEE computer society. https:\/\/doi.org\/10.1109\/ICCV.2017.372","DOI":"10.1109\/ICCV.2017.372"},{"key":"4421_CR49","doi-asserted-by":"publisher","unstructured":"He K, Gkioxari G, Doll\u00e1r P, Girshick RB (2017) Mask r-CNN. In: IEEE international conference on computer vision, ICCV 2017, Italy, october 22-29, 2017, pp 2980\u20132988. IEEE computer society. https:\/\/doi.org\/10.1109\/ICCV.2017.322","DOI":"10.1109\/ICCV.2017.322"},{"key":"4421_CR50","doi-asserted-by":"publisher","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-net: convolutional networks for biomedical image segmentation. In: Navab N, Hornegger J, III WMW, Frangi AF (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th international conference Munich, Germany, October 5 - 9, 2015, Proceedings, Part III, Lecture Notes in Computer Science, vol 9351, pp 234\u2013241. Springer. https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"4421_CR51","doi-asserted-by":"crossref","unstructured":"Zhou P, Han X, Morariu VI, Davis LS (2018) Learning rich features for image manipulation detection. In: 2018 IEEE conference on computer vision and pattern recognition, CVPR 2018, USA, June 18-22, 2018, pp 1053\u20131061. Computer Vision Foundation \/ IEEE Computer Society","DOI":"10.1109\/CVPR.2018.00116"},{"key":"4421_CR52","doi-asserted-by":"crossref","unstructured":"Wu Y, AbdAlmageed W, Natarajan P (2019) Mantra-net: Manipulation tracing network for detection and localization of image forgeries with anomalous features. In: IEEE Conference on computer vision and pattern recognition, CVPR 2019, long beach, CA, USA, June 16-20, 2019, pp 9543\u20139552. Computer Vision Foundation \/ IEEE, DOI 10.1109\/CVPR.2019.00977, (to appear in print)","DOI":"10.1109\/CVPR.2019.00977"},{"key":"4421_CR53","doi-asserted-by":"publisher","unstructured":"Liu N, Han J, Yang M (2018) Picanet: learning pixel-wise contextual attention for saliency detection. In: 2018 IEEE Conference on computer vision and pattern recognition, CVPR 2018, USA, June 18-22, 2018, pp 3089\u20133098. Computer Vision Foundation \/ IEEE Computer Society. https:\/\/doi.org\/10.1109\/CVPR.2018.00326","DOI":"10.1109\/CVPR.2018.00326"},{"key":"4421_CR54","doi-asserted-by":"publisher","unstructured":"Islam A, Long C, Basharat A, Hoogs A (2020) DOA-GAN: dual-order attentive generative adversarial network for image copy-move forgery detection and localization. In: 2020 IEEE\/CVF conference on computer vision and pattern recognition, CVPR 2020, seattle, WA, USA, June 13-19, 2020, pp 4675\u20134684. Computer Vision Foundation \/ IEEE. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00473","DOI":"10.1109\/CVPR42600.2020.00473"},{"key":"4421_CR55","doi-asserted-by":"publisher","unstructured":"Cai Z, Fan Q, Feris RS, Vasconcelos N (2016) A unified multi-scale deep convolutional neural network for fast object detection. In: Leibe B, Matas J, Sebe N, Welling M (eds) Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part IV, Lecture Notes in Computer Science, vol 9908, pp 354\u2013370. Springer. https:\/\/doi.org\/10.1007\/978-3-319-46493-0_22","DOI":"10.1007\/978-3-319-46493-0_22"},{"key":"4421_CR56","doi-asserted-by":"publisher","unstructured":"Zhao J, Liu J, Fan D, Cao Y, Yang J, Cheng M (2019) Egnet: Edge guidance network for salient object detection. In: 2019 IEEE\/CVF international conference on computer vision, ICCV 2019, Korea (South), October 27 - November 2, 2019, pp 8778\u20138787. IEEE. https:\/\/doi.org\/10.1109\/ICCV.2019.00887","DOI":"10.1109\/ICCV.2019.00887"},{"key":"4421_CR57","doi-asserted-by":"publisher","unstructured":"Wu Z, Su L, Huang Q (2019) Stacked cross refinement network for edge-aware salient object detection. In: 2019 IEEE\/CVF international conference on computer vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019, pp 7263\u20137272. IEEE. https:\/\/doi.org\/10.1109\/ICCV.2019.00736","DOI":"10.1109\/ICCV.2019.00736"},{"key":"4421_CR58","doi-asserted-by":"publisher","unstructured":"Fan D, Ji G, Sun G, Cheng M, Shen J, Shao L (2020) Camouflaged object detection. In: 2020 IEEE\/CVF conference on computer vision and pattern recognition, CVPR 2020, USA, June 13-19, 2020, pp 2774\u20132784. Computer Vision Foundation \/ IEEE. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00285","DOI":"10.1109\/CVPR42600.2020.00285"},{"key":"4421_CR59","doi-asserted-by":"crossref","unstructured":"Mei H, Ji G, Wei Z, Yang X, Wei X, Fan D (2021) Camouflaged object segmentation with distraction mining. In: IEEE conference on computer vision and pattern recognition, CVPR 2021, Virtual, June 19-25, 2021, pp 8772\u20138781. Computer vision foundation \/ IEEE","DOI":"10.1109\/CVPR46437.2021.00866"},{"key":"4421_CR60","doi-asserted-by":"publisher","unstructured":"Sun Y, Chen G, Zhou T, Zhang Y, Liu N (2021) Context-aware cross-level fusion network for camouflaged object detection. In: Zhou Z (ed) Proceedings of the thirtieth international joint conference on artificial intelligence, IJCAI 2021, Virtual Event \/ Montreal, Canada, 19-27 August 2021, pp 1025\u20131031. ijcai.org. https:\/\/doi.org\/10.24963\/ijcai.2021\/142","DOI":"10.24963\/ijcai.2021\/142"},{"issue":"2","key":"4421_CR61","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1109\/TPAMI.2019.2938758","volume":"43","author":"SH Gao","year":"2021","unstructured":"Gao SH, Cheng MM, Zhao K, Zhang XY, Yang MH, Torr P (2021) Res2net: a new multi-scale backbone architecture. IEEE Trans Pattern Anal Mach Intell 43(2):652\u2013662. https:\/\/doi.org\/10.1109\/TPAMI.2019.2938758","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4421_CR62","unstructured":"Li W, Zhang Z, Wang X, Luo P (2020) Adax: adaptive gradient descent with exponential long term memory. arXiv:2004.09740"},{"key":"4421_CR63","unstructured":"Ruyong R, Shaozhang N, Hua R, Shubin Z, Tengyue H, Xiaohai T (2022) Esrnet: efficient search and recognition network for image manipulation detection. ACM Trans Multimedia Comput, Commun, Appl (TOMM)"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-04421-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-04421-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-04421-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T03:26:51Z","timestamp":1688700411000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-04421-3"}},"subtitle":["Efficient and robust identification network"],"short-title":[],"issued":{"date-parts":[[2023,1,25]]},"references-count":63,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["4421"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-04421-3","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,25]]},"assertion":[{"value":"19 December 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 January 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}