{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T07:29:13Z","timestamp":1770708553051,"version":"3.49.0"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T00:00:00Z","timestamp":1684972800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T00:00:00Z","timestamp":1684972800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31370710"],"award-info":[{"award-number":["31370710"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds of Central Universities","award":["2572018BF02"],"award-info":[{"award-number":["2572018BF02"]}]},{"name":"Forestry Science and Technology Extension Project","award":["2016[34]"],"award-info":[{"award-number":["2016[34]"]}]},{"name":"the 948 Project from the Ministry of Forestry of China","award":["2014-4-46"],"award-info":[{"award-number":["2014-4-46"]}]},{"DOI":"10.13039\/501100010009","name":"Heilongjiang Provincial Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["LBH-Q13007"],"award-info":[{"award-number":["LBH-Q13007"]}],"id":[{"id":"10.13039\/501100010009","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1007\/s10489-023-04512-9","type":"journal-article","created":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T12:01:59Z","timestamp":1685016119000},"page":"21248-21267","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Giza pyramids construction algorithm with gradient contour approach for multilevel thresholding color image segmentation"],"prefix":"10.1007","volume":"53","author":[{"given":"Bowen","family":"Wu","sequence":"first","affiliation":[]},{"given":"Liangkuan","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,25]]},"reference":[{"key":"4512_CR1","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1109\/TPAMI.2018.2844175","volume":"42","author":"K He","year":"2020","unstructured":"He K, Gkioxari G, Dollar P et al (2020) Mask R CNN. IEEE T Pattern Anal 42:386\u2013397. https:\/\/doi.org\/10.1109\/TPAMI.2018.2844175","journal-title":"IEEE T Pattern Anal"},{"issue":"2","key":"4512_CR2","doi-asserted-by":"publisher","first-page":"260C272","DOI":"10.1109\/TMI.2009.2021946","volume":"29","author":"R Manzke","year":"2010","unstructured":"Manzke R, Meyer C, Ecabert O et al (2010) Automatic segmentation of rotational X-ray images for anatomic intra-procedural surface generation in atrial fibrillation ablation procedures. IEEE T Med Imaging 29 (2):260C272. https:\/\/doi.org\/10.1109\/TMI.2009.2021946","journal-title":"IEEE T Med Imaging"},{"key":"4512_CR3","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.mri.2018.06.015","volume":"54","author":"Y Yang","year":"2018","unstructured":"Yang Y, Tian D, Wu B (2018) A fast and reliable noise-resistant medical image segmentation and bias field correction model. Magn Reson Imaging 54:15\u201331. https:\/\/doi.org\/10.1016\/j.mri.2018.06.015","journal-title":"Magn Reson Imaging"},{"key":"4512_CR4","doi-asserted-by":"publisher","first-page":"402C428","DOI":"10.1007\/s10489-016-0763-5","volume":"45","author":"TM Tuan","year":"2016","unstructured":"Tuan TM, Ngan TT, Son LH (2016) A novel semi-supervised fuzzy clustering method based on interactive fuzzy satisficing for dental x-ray image segmentation. Appl Intell 45:402C428. https:\/\/doi.org\/10.1007\/s10489-016-0763-5","journal-title":"Appl Intell"},{"key":"4512_CR5","doi-asserted-by":"publisher","first-page":"8810C8827","DOI":"10.1007\/s10489-021-02297-3","volume":"51","author":"W Zhao","year":"2021","unstructured":"Zhao W, Lou M, Qi Y et al (2021) Adaptive channel and multiscale spatial context network for breast mass segmentation in full-field mammograms. Appl Intell 51:8810C8827. https:\/\/doi.org\/10.1007\/s10489-021-02297-3","journal-title":"Appl Intell"},{"issue":"3","key":"4512_CR6","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1006\/gmip.1993.1015","volume":"55","author":"M Kamel","year":"1993","unstructured":"Kamel M, Zhao A (1993) Extraction of binary character\/graphics images from grayscale document images. Models Image Process 55(3):203\u2013217. https:\/\/doi.org\/10.1006\/gmip.1993.1015","journal-title":"Models Image Process"},{"key":"4512_CR7","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1109\/TAES.1986.310772","volume":"22","author":"B Bhanu","year":"1986","unstructured":"Bhanu B (1986) Automatic target recognition: state of the art survey. IEEE T Aero Elec Sys 22:364\u2013379. https:\/\/doi.org\/10.1109\/TAES.1986.310772","journal-title":"IEEE T Aero Elec Sys"},{"key":"4512_CR8","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/S0167-8655(99)00142-7","volume":"21","author":"M Sezgin","year":"2000","unstructured":"Sezgin M, Tasaltin R (2000) A new dichotomization technique to multilevel thresholding devoted to inspection applications. Pattern Recogn Lett 21:151\u2013161. https:\/\/doi.org\/10.1016\/S0167-8655(99)00142-7","journal-title":"Pattern Recogn Lett"},{"key":"4512_CR9","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1109\/JSTARS.2019.2961634","volume":"13","author":"S Zhenfeng","year":"2020","unstructured":"Zhenfeng S, Weixun Z, Xueqing D et al (2020) Multilabel remote sensing image retrieval based on fully convolutional network. IEEE J-Stars 13:318\u2013328. https:\/\/doi.org\/10.1109\/JSTARS.2019.2961634","journal-title":"IEEE J-Stars"},{"key":"4512_CR10","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1007\/s12652-017-0673-3","volume":"10","author":"W Farhat","year":"2019","unstructured":"Farhat W, Sghaier H, Faiedh H et al (2019) Design of efficient embedded system for road sign recognition. J Ambient Intell Humaniz Comput 10:491\u2013507. https:\/\/doi.org\/10.1007\/s12652-017-0673-3","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"4512_CR11","doi-asserted-by":"publisher","first-page":"1701C1732","DOI":"10.1007\/s10489-020-01903-0","volume":"51","author":"SBB Ahmadi","year":"2020","unstructured":"Ahmadi SBB, Zhang G, Rabbani M et al (2020) An intelligent and blind dual color image watermarking for authentication and copyright protection. Appl Intell 51:1701C1732. https:\/\/doi.org\/10.1007\/s10489-020-01903-0","journal-title":"Appl Intell"},{"key":"4512_CR12","doi-asserted-by":"publisher","first-page":"105570","DOI":"10.1016\/j.knosys.2020.105570","volume":"194","author":"ZK Xing","year":"2020","unstructured":"Xing ZK (2020) An improved emperor penguin optimization based multilevel thresholding for color image segmentation. Knowl-Based Syst 194:105570. https:\/\/doi.org\/10.1016\/j.knosys.2020.105570","journal-title":"Knowl-Based Syst"},{"key":"4512_CR13","doi-asserted-by":"publisher","unstructured":"Houssein EH, Neggaz N, Hosney ME, Mohamed WM, Hassaballah M (2021) Enhanced Harris hawks optimization with genetic operators for selection chemical descriptors and compounds activities Neural Comput Appl 1C18. https:\/\/doi.org\/10.1007\/s00521-021-05991-y","DOI":"10.1007\/s00521-021-05991-y"},{"issue":"14","key":"4512_CR14","doi-asserted-by":"publisher","first-page":"10759C10771","DOI":"10.1007\/s00521-019-04611-0","volume":"32","author":"FA Hashim","year":"2020","unstructured":"Hashim FA, Houssein EH, Hussain K et al (2020) A modified henry gas solubility optimization for solving motif discovery problem. Neural Comput Appl 32(14):10759C10771. https:\/\/doi.org\/10.1007\/s00521-019-04611-0","journal-title":"Neural Comput Appl"},{"issue":"12","key":"4512_CR15","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1007\/s00521-016-2645-5","volume":"29","author":"SC Satapathy","year":"2018","unstructured":"Satapathy SC, Raja NSM, Rajinikanth V et al (2018) Multi-level image thresholding using Otsu and chaotic bat algorithm. Neural Comput Appl 29(12):1285\u20131307. https:\/\/doi.org\/10.1007\/s00521-016-2645-5","journal-title":"Neural Comput Appl"},{"issue":"12","key":"4512_CR16","doi-asserted-by":"publisher","first-page":"2290","DOI":"10.1007\/10.1109\/TPAMI.2009.96","volume":"31","author":"A Levinshtein","year":"2009","unstructured":"Levinshtein A, Stere A, Kutulakos KN, et al. (2009) Turbopixels: fast superpixels using geometric flows. IEEE T Pattern Anal 31(12):2290\u20132297. https:\/\/doi.org\/10.1007\/10.1109\/TPAMI.2009.96","journal-title":"IEEE T Pattern Anal"},{"key":"4512_CR17","doi-asserted-by":"publisher","first-page":"1501","DOI":"10.3390\/rs12091501","volume":"12","author":"C He","year":"2020","unstructured":"He C, Li S, Xiong D (2020) Remote sensing image semantic segmentation based on edge information guidance. Remote Sens 12:1501. https:\/\/doi.org\/10.3390\/rs12091501","journal-title":"Remote Sens"},{"key":"4512_CR18","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1109\/TPAMI.2018.2876253","volume":"42","author":"M Keuper","year":"2020","unstructured":"Keuper M, Tang S, Andres B et al (2020) Motion Segmentation and Multiple Object Tracking by Correlation Co-Clustering. IEEE T Pattern Anal 42:140\u2013153. https:\/\/doi.org\/10.1109\/TPAMI.2018.2876253","journal-title":"IEEE T Pattern Anal"},{"key":"4512_CR19","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1109\/JSTARS.2019.2961634","volume":"13","author":"Z Shao","year":"2020","unstructured":"Shao Z, Zhou W, Deng X, et al. (2020) Multilabel remote sensing image retrieval based on fully convolutional network. IEEE J-Stars 13:318\u2013328. https:\/\/doi.org\/10.1109\/JSTARS.2019.2961634","journal-title":"IEEE J-Stars"},{"key":"4512_CR20","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1109\/TMI.2019.2959609","volume":"42","author":"Z Zhou","year":"2020","unstructured":"Zhou Z, Siddiquee MMR, Tajbakhsh N, et al. (2020) UNet plus plus: redesigning skip connections to exploit multiscale features in image segmentation. IEEE T Med Imaging 42:140\u2013153. https:\/\/doi.org\/10.1109\/TMI.2019.2959609","journal-title":"IEEE T Med Imaging"},{"key":"4512_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cviu.2017.03.007","volume":"166","author":"D Stutz","year":"2018","unstructured":"Stutz D, Hermans A, Leibe B (2018) Superpixels: an evaluation of the state-of-the-art. Comput Vis Image Und 166:1\u201327. https:\/\/doi.org\/10.1016\/j.cviu.2017.03.007","journal-title":"Comput Vis Image Und"},{"key":"4512_CR22","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.jvcir.2015.09.015","volume":"33","author":"M Ciecholewski","year":"2015","unstructured":"Ciecholewski M (2015) Automated coronal hole segmentation from Solar EUV images using the watershed transform. J Vis Commun Image R 33:203\u2013218. https:\/\/doi.org\/10.1016\/j.jvcir.2015.09.015","journal-title":"J Vis Commun Image R"},{"key":"4512_CR23","doi-asserted-by":"publisher","first-page":"925C939","DOI":"10.1109\/TPAMI.2009.71","volume":"32","author":"J Cousty","year":"2010","unstructured":"Cousty J, Bertrand G, Najman L et al (2010) Watershed cuts: thinnings, shortest path forests, and topological watersheds. IEEE T Pattern Anal 32:925C939. https:\/\/doi.org\/10.1109\/TPAMI.2009.71","journal-title":"IEEE T Pattern Anal"},{"key":"4512_CR24","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.eswa.2019.01.031","volume":"123","author":"F Breve","year":"2019","unstructured":"Breve F (2019) Interactive image segmentation using label propagation through complex networks. Expert Syst Appl 123:18\u201333. https:\/\/doi.org\/10.1016\/j.eswa.2019.01.031","journal-title":"Expert Syst Appl"},{"key":"4512_CR25","doi-asserted-by":"publisher","first-page":"18","DOI":"10.3390\/e21030318","volume":"123","author":"C Lang","year":"2019","unstructured":"Lang C, Jia H (2019) Kapurs entropy for color image segmentation based on a hybrid whale optimization algorithm. Entropy-Switz 123:18\u201333. https:\/\/doi.org\/10.3390\/e21030318","journal-title":"Entropy-Switz"},{"key":"4512_CR26","doi-asserted-by":"publisher","first-page":"106510","DOI":"10.1016\/j.knosys.2020.106510","volume":"216","author":"D Zhao","year":"2021","unstructured":"Zhao D, Liu L, Yu F, et al. (2021) Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy. Knowl-Based Syst 216:106510. https:\/\/doi.org\/10.1016\/j.knosys.2020.106510","journal-title":"Knowl-Based Syst"},{"key":"4512_CR27","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1109\/JSTSP.2019.2939998","volume":"14","author":"AD Back","year":"2020","unstructured":"Back AD, Angus D, Wiles J (2020) Transitive entropy-a rank ordered approach for natural sequences. IEEE J-STSP 14:312\u2013321. https:\/\/doi.org\/10.1109\/JSTSP.2019.2939998","journal-title":"IEEE J-STSP"},{"key":"4512_CR28","doi-asserted-by":"publisher","first-page":"114327","DOI":"10.1016\/j.eswa.2020.114327","volume":"169","author":"C Wu","year":"2021","unstructured":"Wu C, Cao Z (2021) Entropy-like divergence based kernel fuzzy clustering for robust image segmentation. Expert Syst Appl 169:114327. https:\/\/doi.org\/10.1016\/j.eswa.2020.114327","journal-title":"Expert Syst Appl"},{"issue":"3","key":"4512_CR29","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1007\/s00521-016-2482-6","volume":"29","author":"RB Oliveira","year":"2018","unstructured":"Oliveira RB, Papa JP, Pereira AS (2018) Computational methods for pigmented skin lesion classification in images: review and future trends. Neural Comput Appl 29(3):613\u2013636. https:\/\/doi.org\/10.1007\/s00521-016-2482-6","journal-title":"Neural Comput Appl"},{"issue":"13","key":"4512_CR30","doi-asserted-by":"publisher","first-page":"9521C9543","DOI":"10.1007\/s00521-019-04465-6","volume":"32","author":"S Gupta","year":"2020","unstructured":"Gupta S, Deep K (2020) Hybrid sine cosine artificial bee colony algorithm for global optimization and image segmentation. Neural Comput Appl 32(13):9521C9543. https:\/\/doi.org\/10.1007\/s00521-019-04465-6","journal-title":"Neural Comput Appl"},{"key":"4512_CR31","doi-asserted-by":"publisher","first-page":"1C34","DOI":"10.1007\/s00521-020-04820-y","volume":"1","author":"M Abdel-Basset","year":"2020","unstructured":"Abdel-Basset M, Chang V, Mohamed R (2020) A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems. Neural Comput Appl 1:1C34. https:\/\/doi.org\/10.1007\/s00521-020-04820-y","journal-title":"Neural Comput Appl"},{"issue":"3","key":"4512_CR32","doi-asserted-by":"publisher","first-page":"855","DOI":"10.1007\/s11831-019-09334-y","volume":"27","author":"KG Dhal","year":"2019","unstructured":"Dhal KG, Das A, Rag S, et al. (2019) Nature-inspired optimization algorithms and their application in multi-thresholding image segmentation. Arch Comput Method E 27(3):855\u2013888. https:\/\/doi.org\/10.1007\/s11831-019-09334-y","journal-title":"Arch Comput Method E"},{"key":"4512_CR33","doi-asserted-by":"publisher","first-page":"570","DOI":"10.1016\/j.asoc.2017.08.039","volume":"61","author":"S Pare","year":"2017","unstructured":"Pare S, Kumar A, Bajaj V (2017) An efficient method for multilevel color image thresholding using cuckoo search algorithm based on minimum cross entropy. Appl Soft Comput 61:570\u2013592. https:\/\/doi.org\/10.1016\/j.asoc.2017.08.039","journal-title":"Appl Soft Comput"},{"key":"4512_CR34","doi-asserted-by":"publisher","first-page":"14122","DOI":"10.1016\/j.eswa.2020.114122","volume":"167","author":"D Zhao","year":"2020","unstructured":"Zhao D, Liu L, Yu F, Heidari AA, et al. (2020) Ant colony optimization with horizontal and vertical crossover search: fundamental visions for multi-threshold image segmentation. Expert Syst Appl 167:14122. https:\/\/doi.org\/10.1016\/j.eswa.2020.114122","journal-title":"Expert Syst Appl"},{"key":"4512_CR35","doi-asserted-by":"publisher","first-page":"113428","DOI":"10.1016\/j.eswa.2020.113428","volume":"155","author":"E Rodriguez-Esparza","year":"2020","unstructured":"Rodriguez-Esparza E, Zanella-Calzada LA, Oliva D et al (2020) An efficient Harris hawks-inspired image segmentation method. Expert Syst Appl 155:113428. https:\/\/doi.org\/10.1016\/j.eswa.2020.113428","journal-title":"Expert Syst Appl"},{"key":"4512_CR36","doi-asserted-by":"publisher","first-page":"960C978","DOI":"10.1007\/s10489-011-0307-y","volume":"36","author":"S Mirghasemi","year":"2012","unstructured":"Mirghasemi S, Yazdi HS, Lotfizad M (2012) A target-based color space for sea target detection. Appl Intell 36:960C978. https:\/\/doi.org\/10.1007\/s10489-011-0307-y","journal-title":"Appl Intell"},{"issue":"16","key":"4512_CR37","doi-asserted-by":"publisher","first-page":"12011C12031","DOI":"10.1007\/s00521-019-04210-z","volume":"32","author":"Z Yang","year":"2020","unstructured":"Yang Z, Angus W (2020) A non-revisiting quantum-behaved particle swarm optimization based multilevel thresholding for image segmentation. Neural Comput Appl 32(16):12011C12031. https:\/\/doi.org\/10.1007\/s00521-019-04210-z","journal-title":"Neural Comput Appl"},{"key":"4512_CR38","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) The ant lion optimizer. Adv Eng Softw 83:80\u201398. https:\/\/doi.org\/10.1016\/j.advengsoft.2015.01.010","journal-title":"Adv Eng Softw"},{"key":"4512_CR39","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","volume":"89","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl-Based Syst 89:228\u2013249. https:\/\/doi.org\/10.1016\/j.knosys.2015.07.006","journal-title":"Knowl-Based Syst"},{"key":"4512_CR40","doi-asserted-by":"publisher","first-page":"32805","DOI":"10.1109\/ACCESS.2019.2903345","volume":"7","author":"H Jia","year":"2019","unstructured":"Jia H, Peng X, Song W et al (2019) Multiverse optimization algorithm based on levy flight improvement for multithreshold color image segmentation. IEEE Access 7:32805\u201332844. https:\/\/doi.org\/10.1109\/ACCESS.2019.2903345","journal-title":"IEEE Access"},{"key":"4512_CR41","doi-asserted-by":"publisher","first-page":"106552","DOI":"10.1016\/j.knosys.2020.106552","volume":"211","author":"D Wei","year":"2021","unstructured":"Wei D, Wang Z, Si L et al (2021) Preaching-inspired swarm intelligence algorithm and its applications. Knowl-Based Syst 211:106552. https:\/\/doi.org\/10.1016\/j.knosys.2020.106552","journal-title":"Knowl-Based Syst"},{"key":"4512_CR42","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1016\/j.knosys.2018.12.008","volume":"165","author":"S Gupta","year":"2019","unstructured":"Gupta S, Deep K (2019) Improved sine cosine algorithm with crossover scheme for global optimization. Knowl-Based Syst 165:374\u2013406. https:\/\/doi.org\/10.1016\/j.knosys.2018.12.008","journal-title":"Knowl-Based Syst"},{"key":"4512_CR43","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.eswa.2017.04.023","volume":"83","author":"MAE Aziz","year":"2017","unstructured":"Aziz MAE, Ewees AA, Hassanien AE (2017) Whale Optimization Algorithm and Moth-Flame Optimization for multilevel thresholding image segmentation. Expert Syst Appl 83:242\u2013256. https:\/\/doi.org\/10.1016\/j.eswa.2017.04.023","journal-title":"Expert Syst Appl"},{"key":"4512_CR44","doi-asserted-by":"publisher","first-page":"770C782","DOI":"10.1016\/j.asoc.2017.05.019","volume":"58","author":"Y Pan","year":"2017","unstructured":"Pan Y, Xia Y, Zhou T et al (2017) Cell image segmentation using bacterial foraging optimization. Appl Soft Comput 58:770C782. https:\/\/doi.org\/10.1016\/j.asoc.2017.05.019","journal-title":"Appl Soft Comput"},{"key":"4512_CR45","doi-asserted-by":"publisher","first-page":"16681C16706","DOI":"10.1007\/s00521-020-04989-2","volume":"32","author":"S Singh","year":"2020","unstructured":"Singh S, Mittal N, Singh H (2020) A multilevel thresholding algorithm using LebTLBO for image segmentation. Neural Comput Appl 32:16681C16706. https:\/\/doi.org\/10.1007\/s00521-020-04989-2","journal-title":"Neural Comput Appl"},{"issue":"9","key":"4512_CR46","doi-asserted-by":"publisher","first-page":"4583","DOI":"10.1007\/s00521-018-3771-z","volume":"32","author":"KB Ashish","year":"2020","unstructured":"Ashish KB (2020) A novel beta differential evolution algorithm-based fast multilevel thresholding for color image segmentation. Neural Comput Appl 32(9):4583\u20134613. https:\/\/doi.org\/10.1007\/s00521-018-3771-z","journal-title":"Neural Comput Appl"},{"key":"4512_CR47","doi-asserted-by":"publisher","first-page":"10057C10091","DOI":"10.1007\/s00521-021-05771-8","volume":"33","author":"A Omar","year":"1005","unstructured":"Omar A, Ernesto A, Fernando W, Marco PC (1005) An accurate Cluster chaotic optimization approach for digital medical image segmentation. Neural Comput Appl 33:10057C10091. https:\/\/doi.org\/10.1007\/s00521-021-05771-8","journal-title":"Neural Comput Appl"},{"issue":"1","key":"4512_CR48","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1109\/TEVC.2018.2808689","volume":"23","author":"Y Sun","year":"2018","unstructured":"Sun Y, Yen GG, Yi Z (2018) Evolving unsupervised deep neural networks for learning meaningful representations. IEEE T Evolut Comput 23(1):89\u2013103. https:\/\/doi.org\/10.1109\/TEVC.2018.2808689","journal-title":"IEEE T Evolut Comput"},{"issue":"5","key":"4512_CR49","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1109\/TEVC.2021.3130835","volume":"26","author":"M Omidvar","year":"2021","unstructured":"Omidvar M, Li X, Yao X (2021) A review of population-based metaheuristics for large-scale black-box global optimization: Part B. IEEE T Evolut Comput 26(5):823\u2013843. https:\/\/doi.org\/10.1109\/TEVC.2021.3130835","journal-title":"IEEE T Evolut Comput"},{"issue":"6","key":"4512_CR50","doi-asserted-by":"publisher","first-page":"1667","DOI":"10.1109\/TMAG.2011.2106218","volume":"47","author":"DK Woo","year":"2011","unstructured":"Woo DK, Choi JH, Ali M, et al. (2011) A novel multimodal optimization algorithm applied to electromagnetic optimization. IEEE T Magn 47(6):1667\u20131673. https:\/\/doi.org\/10.1109\/TMAG.2011.2106218","journal-title":"IEEE T Magn"},{"issue":"2","key":"4512_CR51","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1109\/TEVC.2019.2925175","volume":"24","author":"Y Zheng","year":"2019","unstructured":"Zheng Y, Du Y, Ling H et al (2019) Evolutionary collaborative human-UAV search for escaped criminals. IEEE T Evolut Comput 24(2):217\u2013231. https:\/\/doi.org\/10.1109\/TEVC.2019.2925175","journal-title":"IEEE T Evolut Comput"},{"issue":"4","key":"4512_CR52","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1109\/TEVC.2017.2742502","volume":"22","author":"F Zaman","year":"2017","unstructured":"Zaman F, Elsayed SM, Ray T, et al. (2017) Evolutionary algorithms for finding Nash equilibria in electricity markets. IEEE T Evolut Comput 22(4):536\u2013549. https:\/\/doi.org\/10.1109\/TEVC.2017.2742502","journal-title":"IEEE T Evolut Comput"},{"issue":"14","key":"4512_CR53","doi-asserted-by":"publisher","first-page":"1743","DOI":"10.1007\/s12065-020-00451-3","volume":"4","author":"S Harifi","year":"2021","unstructured":"Harifi S, Mohammadzadeh J, Khalilian M, et al. (2021) Giza pyramids Construction: an ancient-inspired metaheuristic algorithm for optimization. Evol Comput 4(14):1743\u20131761. https:\/\/doi.org\/10.1007\/s12065-020-00451-3","journal-title":"Evol Comput"},{"key":"4512_CR54","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s12559-016-9442-4","volume":"9","author":"B Song","year":"2017","unstructured":"Song B, Wang Z, Zou L (2017) On global smooth path planning for mobile robots using a novel multimodal delayed PSO algorithm. Cogn Comput 9:5\u201317. https:\/\/doi.org\/10.1007\/s12559-016-9442-4","journal-title":"Cogn Comput"},{"key":"4512_CR55","doi-asserted-by":"publisher","unstructured":"Lin Y, Zhang J, Lan L (2008) A contour method in population-based stochastic algorithms. In: Proceedings of the 2008 IEEE congress on evolutionary computation. IEEE, pp 2388\u20132395. https:\/\/doi.org\/10.1109\/CEC.2008.4631117","DOI":"10.1109\/CEC.2008.4631117"},{"issue":"24","key":"4512_CR56","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1109\/TEVC.2019.2910721","volume":"1","author":"Z Wang","year":"2020","unstructured":"Wang Z, Zhan Z, Lin Y et al (2020) Automatic Niching differential evolution with contour prediction approach for Multimodal optimization problems. IEEE T Evolut Comput 1(24):124\u2013128. https:\/\/doi.org\/10.1109\/TEVC.2019.2910721","journal-title":"IEEE T Evolut Comput"},{"key":"4512_CR57","doi-asserted-by":"publisher","unstructured":"Zhang MJ, Smart W (2004) Genetic programming with gradient descent search for multiclass object classification. In: Proceedings of the 7th European conference on genetic programming. Springer, pp 399\u2013408. https:\/\/doi.org\/10.1007\/978-3-540-24650-338","DOI":"10.1007\/978-3-540-24650-338"},{"issue":"5786","key":"4512_CR58","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Salakhutdinov RR (2006) Reducing the dimensionality of data with neural networks. Science 313(5786):504\u2013507. https:\/\/doi.org\/10.1126\/science.1127647","journal-title":"Science"},{"issue":"9","key":"4512_CR59","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"1","author":"NA Otsu","year":"2007","unstructured":"Otsu NA (2007) Threshold selection method from gray-level histograms. IEEE T Syst Man Cy-S 1(9):62\u201366. https:\/\/doi.org\/10.1109\/TSMC.1979.4310076","journal-title":"IEEE T Syst Man Cy-S"},{"key":"4512_CR60","doi-asserted-by":"publisher","first-page":"107468","DOI":"10.1016\/j.knosys.2021.107468","volume":"232","author":"R Bandopadhyay","year":"2021","unstructured":"Bandopadhyay R, Kundu R, Oliva D (2021) Segmentation of brain mri using an altruistic harris hawks optimization algorithm. Knowl-Based Syst 232:107468. https:\/\/doi.org\/10.1016\/j.knosys.2021.107468","journal-title":"Knowl-Based Syst"},{"issue":"2","key":"4512_CR61","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1109\/tpami.1985.4767640","volume":"7","author":"MD Levine","year":"1985","unstructured":"Levine MD, Nazif AM (1985) Dynamic measurement of computer generated image segmentations. IEEE T Pattern Anal 7(2):155\u2013164. https:\/\/doi.org\/10.1109\/tpami.1985.4767640","journal-title":"IEEE T Pattern Anal"},{"key":"4512_CR62","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/0734-189X(88)90022-9","volume":"41","author":"PK Sahoo","year":"1988","unstructured":"Sahoo PK, Soltani S, Wong AKC (1988) A survey of thresholding techniques. Graph Models 41:233\u2013260. https:\/\/doi.org\/10.1016\/0734-189X(88)90022-9","journal-title":"Graph Models"},{"issue":"110","key":"4512_CR63","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.cviu.2007.08.003","volume":"2","author":"H Zhang","year":"2008","unstructured":"Zhang H, Fritts JE, Goldman SA (2008) Image segmentation evaluation: a survey of unsupervised methods. Comput Vis Image Und 2(110):260\u2013280. https:\/\/doi.org\/10.1016\/j.cviu.2007.08.003","journal-title":"Comput Vis Image Und"},{"key":"4512_CR64","doi-asserted-by":"crossref","unstructured":"Rosenberger C, Chabrier S, Laurent H, Emile B (2006) Unsupervised and supervised image segmentation evaluation. In: Zhang YJ (ed) Advances in image and video segmentation, IRM Press: Pennsylvania, USA, vol 18, pp 365C393","DOI":"10.4018\/978-1-59140-753-9.ch018"},{"issue":"1","key":"4512_CR65","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/S0734-189X(85)90156-2","volume":"29","author":"JN Kapur","year":"1985","unstructured":"Kapur JN, Sahoo PK, Wong AKC (1985) A new method for gray-level picture thresholding using the entropy of histogram. Graph Models 29(1):273\u2013285. https:\/\/doi.org\/10.1016\/S0734-189X(85)90156-2","journal-title":"Graph Models"},{"issue":"6","key":"4512_CR66","doi-asserted-by":"publisher","first-page":"522","DOI":"10.3969\/j.issn.1673-4785.2010.06.009","volume":"5","author":"Y Wu","year":"2010","unstructured":"Wu Y, Ji S (2010) Multi threshold selection for an image based on gray entropy and chaotic particle swarm optimization. CAAI Transactions on Intelligence Systems 5(6):522\u2013529. https:\/\/doi.org\/10.3969\/j.issn.1673-4785.2010.06.009","journal-title":"CAAI Transactions on Intelligence Systems"},{"issue":"4","key":"4512_CR67","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1016\/0031-3203(93)90115-D","volume":"29","author":"CH Li","year":"1996","unstructured":"Li CH, Lee CK (1996) Minimum cross entropy thresholding. Pattern Recogn 29(4):575\u2013580. https:\/\/doi.org\/10.1016\/0031-3203(93)90115-D","journal-title":"Pattern Recogn"},{"key":"4512_CR68","doi-asserted-by":"publisher","first-page":"937","DOI":"10.1016\/j.ins.2005.02.003","volume":"176","author":"F Bergh","year":"2005","unstructured":"Bergh F, Engelbrecht AP (2005) A study of particle swarm optimization particle trajectories. Inform Sciences 176:937\u2013971. https:\/\/doi.org\/10.1016\/j.ins.2005.02.003","journal-title":"Inform Sciences"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-023-04512-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-023-04512-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-023-04512-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T11:15:00Z","timestamp":1695122100000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-023-04512-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,25]]},"references-count":68,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2023,9]]}},"alternative-id":["4512"],"URL":"https:\/\/doi.org\/10.1007\/s10489-023-04512-9","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,25]]},"assertion":[{"value":"6 February 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 May 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"standard This article does not contain any studies with human participants or animals performed by any of the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Ethics"}},{"value":"The authors declare no conflict of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}