{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:25:39Z","timestamp":1740122739607,"version":"3.37.3"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,11,15]],"date-time":"2022-11-15T00:00:00Z","timestamp":1668470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,11,15]],"date-time":"2022-11-15T00:00:00Z","timestamp":1668470400000},"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":["Neural Process Lett"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s11063-022-11088-x","type":"journal-article","created":{"date-parts":[[2022,11,15]],"date-time":"2022-11-15T20:20:49Z","timestamp":1668543649000},"page":"5215-5243","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Biomedical Image Segmentation Using Fuzzy Artificial Cell Swarm Optimization (FACSO)"],"prefix":"10.1007","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3427-7492","authenticated-orcid":false,"given":"Shouvik","family":"Chakraborty","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kalyani","family":"Mali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,15]]},"reference":[{"key":"11088_CR1","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/s11831-019-09324-0","volume":"27","author":"SS Chouhan","year":"2020","unstructured":"Chouhan SS, Singh UP, Jain S (2020) Applications of computer vision in plant pathology: a survey. Arch Comput Methods Eng 27:611\u2013632. https:\/\/doi.org\/10.1007\/s11831-019-09324-0","journal-title":"Arch Comput Methods Eng"},{"key":"11088_CR2","doi-asserted-by":"crossref","unstructured":"Baldner FDO, Costa PB, Gomes JFS, Leta FR (2020) A review on computer vision applied to mechanical tests in search for better accuracy. In: Lecture notes in mechanical engineering. Springer, pp 265\u2013281","DOI":"10.1007\/978-981-13-9806-3_9"},{"key":"11088_CR3","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Mali K (2020) An overview of biomedical image analysis from the deep learning perspective. In: Chakraborty S, Mali K (eds) Applications of advanced machine intelligence in computer vision and object recognition: emerging research and opportunities. IGI Global","DOI":"10.4018\/978-1-7998-2736-8.ch008"},{"key":"11088_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2019.100980","volume":"43","author":"W Fang","year":"2020","unstructured":"Fang W, Love PED, Luo H, Ding L (2020) Computer vision for behaviour-based safety in construction: a review and future directions. Adv Eng Inform 43:100980","journal-title":"Adv Eng Inform"},{"key":"11088_CR5","doi-asserted-by":"crossref","unstructured":"Roy M, Chakraborty S, Mali K (2020) A robust image encryption method using chaotic skew-tent map. In: Chakraborty S, Mali K (eds) Applications of advanced machine intelligence in computer vision and object recognition: emerging research and opportunities","DOI":"10.4018\/978-1-7998-2736-8.ch001"},{"key":"11088_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2019.103013","volume":"110","author":"W Fang","year":"2020","unstructured":"Fang W, Ding L, Love PED et al (2020) Computer vision applications in construction safety assurance. Autom Constr 110:103013","journal-title":"Autom Constr"},{"key":"11088_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/S13662-020-02566-4\/FIGURES\/4","volume":"2020","author":"J Zhang","year":"2020","unstructured":"Zhang J, Huang C (2020) Dynamics analysis on a class of delayed neural networks involving inertial terms. Adv Differ Equ 2020:1\u201312. https:\/\/doi.org\/10.1186\/S13662-020-02566-4\/FIGURES\/4","journal-title":"Adv Differ Equ"},{"key":"11088_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/S13662-020-02737-3\/FIGURES\/2","volume":"2020","author":"H Zhang","year":"2020","unstructured":"Zhang H, Qian C (2020) Convergence analysis on inertial proportional delayed neural networks. Adv Differ Equ 2020:1\u201310. https:\/\/doi.org\/10.1186\/S13662-020-02737-3\/FIGURES\/2","journal-title":"Adv Differ Equ"},{"issue":"5","key":"11088_CR9","doi-asserted-by":"publisher","first-page":"3378","DOI":"10.3934\/MATH.2020218","volume":"43378","author":"C Huang","year":"2020","unstructured":"Huang C, Yang L, Cao J et al (2020) Asymptotic behavior for a class of population dynamics. AIMS Math 43378(5):3378\u20133390. https:\/\/doi.org\/10.3934\/MATH.2020218","journal-title":"AIMS Math"},{"key":"11088_CR10","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1588\/namc.2020.25.16775","volume":"25","author":"I Manickam","year":"2020","unstructured":"Manickam I, Ramachandran R, Rajchakit G et al (2020) Novel Lagrange sense exponential stability criteria for time-delayed stochastic Cohen-Grossberg neural networks with Markovian jump parameters: a graph-theoretic approach. Nonlinear Anal Model Control 25:726\u2013744. https:\/\/doi.org\/10.1588\/namc.2020.25.16775","journal-title":"Nonlinear Anal Model Control"},{"key":"11088_CR11","doi-asserted-by":"crossref","unstructured":"Chakraborty S (2020) An advanced approach to detect edges of digital images for image segmentation. In: Chakraborty S, Mali K (eds) Applications of advanced machine intelligence in computer vision and object recognition: emerging research and opportunities. IGI GLobal","DOI":"10.4018\/978-1-7998-2736-8.ch004"},{"key":"11088_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1088\/0031-9155\/58\/13\/R97","volume":"58","author":"S Bauer","year":"2013","unstructured":"Bauer S, Wiest R, Nolte LP, Reyes M (2013) A survey of MRI-based medical image analysis for brain tumor studies. Phys Med Biol 58:1","journal-title":"Phys Med Biol"},{"key":"11088_CR13","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Mali K (2018) Application of multiobjective optimization techniques in biomedical image segmentation\u2014a study. In: Multi-objective optimization. Springer, Singapore, pp 181\u2013194","DOI":"10.1007\/978-981-13-1471-1_8"},{"key":"11088_CR14","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Roy M, Hore S (2016) A study on different edge detection techniques in digital image processing. In: Feature detectors and motion detection in video processing. IGI Global, pp 100\u2013122","DOI":"10.4018\/978-1-5225-1025-3.ch005"},{"key":"11088_CR15","doi-asserted-by":"publisher","first-page":"2773","DOI":"10.11591\/ijece.v6i6.11801","volume":"6","author":"S Hore","year":"2016","unstructured":"Hore S, Chakraborty S, Chatterjee S et al (2016) An integrated interactive technique for image segmentation using stack based seeded region growing and thresholding. Int J Electr Comput Eng 6:2773\u20132780. https:\/\/doi.org\/10.11591\/ijece.v6i6.11801","journal-title":"Int J Electr Comput Eng"},{"key":"11088_CR16","first-page":"299","volume-title":"A biomedical image segmentation approach using fractional order darwinian particle swarm optimization and thresholding","author":"S Chakraborty","year":"2021","unstructured":"Chakraborty S, Mali K, Banerjee A, Bhattacharjee M (2021) A biomedical image segmentation approach using fractional order darwinian particle swarm optimization and thresholding. Springer, Singapore, pp 299\u2013306"},{"key":"11088_CR17","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Mali K, Ghosh K, Sarkar A (2021) Penalized fuzzy C-means coupled level set based biomedical image segmentation. In: Lecture notes in networks and systems. Springer Science and Business Media Deutschland GmbH, pp 279\u2013287","DOI":"10.1007\/978-981-15-9433-5_27"},{"key":"11088_CR18","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Chatterjee S, Ashour AS, et al (2017) Intelligent computing in medical imaging: a study. In: Dey N (ed) Advancements in applied metaheuristic computing. IGI Global, pp 143\u2013163","DOI":"10.4018\/978-1-5225-4151-6.ch006"},{"key":"11088_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/S10115-022-01659-8","volume":"2022","author":"S Chakraborty","year":"2022","unstructured":"Chakraborty S, Mali K (2022) Fuzzy modified cuckoo search for biomedical image segmentation. Knowl Inf Syst 2022:1\u201340. https:\/\/doi.org\/10.1007\/S10115-022-01659-8","journal-title":"Knowl Inf Syst"},{"key":"11088_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/s11517-020-02135-7","author":"M Sharma","year":"2020","unstructured":"Sharma M, Bhattacharya M (2020) Discrimination and quantification of live\/dead rat brain cells using a non-linear segmentation model. Med Biol Eng Comput. https:\/\/doi.org\/10.1007\/s11517-020-02135-7","journal-title":"Med Biol Eng Comput"},{"key":"11088_CR21","doi-asserted-by":"publisher","first-page":"24454","DOI":"10.1038\/srep24454","volume":"6","author":"J-Z Cheng","year":"2016","unstructured":"Cheng J-Z, Ni D, Chou Y-H et al (2016) Computer-aided diagnosis with deep learning architecture: applications to breast lesions in US images and pulmonary nodules in CT scans. Sci Rep 6:24454. https:\/\/doi.org\/10.1038\/srep24454","journal-title":"Sci Rep"},{"key":"11088_CR22","doi-asserted-by":"publisher","DOI":"10.1201\/9780429318078-3\/PREPROCESSING-DISCRIMINATION-CYTOPATHOLOGICAL-IMAGES-SHOUVIK-CHAKRABORTY-KALYANI-MALI-SANKHADEEP-CHATTERJEE-SOUMYA-SEN","author":"S Chakraborty","year":"2021","unstructured":"Chakraborty S, Mali K, Chatterjee S, Sen S (2021) Preprocessing and discrimination of cytopathological images. Med Internet Things Tech Pract Appl. https:\/\/doi.org\/10.1201\/9780429318078-3\/PREPROCESSING-DISCRIMINATION-CYTOPATHOLOGICAL-IMAGES-SHOUVIK-CHAKRABORTY-KALYANI-MALI-SANKHADEEP-CHATTERJEE-SOUMYA-SEN","journal-title":"Med Internet Things Tech Pract Appl"},{"key":"11088_CR23","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Chatterjee S, Das A, Mali K (2020) Penalized fuzzy C-means enabled hybrid region growing in segmenting medical images. pp 41\u201365","DOI":"10.1007\/978-981-13-8930-6_3"},{"key":"11088_CR24","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1109\/3468.668967","volume":"28","author":"YA Tolias","year":"1998","unstructured":"Tolias YA, Panas SM (1998) Image segmentation by a fuzzy clustering algorithm using adaptive spatially constrained membership functions. IEEE Trans Syst Man Cybern Part A Syst Hum 28:359\u2013369. https:\/\/doi.org\/10.1109\/3468.668967","journal-title":"IEEE Trans Syst Man Cybern Part A Syst Hum"},{"key":"11088_CR25","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/0098-3004(84)90020-7","volume":"10","author":"JC Bezdek","year":"1984","unstructured":"Bezdek JC, Ehrlich R, Full W (1984) FCM: The fuzzy c-means clustering algorithm. Comput Geosci 10:191\u2013203. https:\/\/doi.org\/10.1016\/0098-3004(84)90020-7","journal-title":"Comput Geosci"},{"key":"11088_CR26","doi-asserted-by":"crossref","unstructured":"Castillo O, Melin P, Kacprzyk J, Pedrycz W (2008) Type-2 fuzzy logic: theory and applications. Institute of Electrical and Electronics Engineers (IEEE), pp 145\u2013145","DOI":"10.1109\/GrC.2007.118"},{"key":"11088_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/J.ASOC.2022.108528","volume":"119","author":"S Chakraborty","year":"2022","unstructured":"Chakraborty S, Mali K (2022) A radiological image analysis framework for early screening of the COVID-19 infection: a computer vision-based approach. Appl Soft Comput 119:108528. https:\/\/doi.org\/10.1016\/J.ASOC.2022.108528","journal-title":"Appl Soft Comput"},{"key":"11088_CR28","first-page":"196","volume-title":"Artificial cell swarm optimization","author":"S Chatterjee","year":"2020","unstructured":"Chatterjee S, Dawn S, Hore S (2020) Artificial cell swarm optimization. Springer, Singapore, pp 196\u2013214"},{"key":"11088_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102800","author":"S Chakraborty","year":"2021","unstructured":"Chakraborty S, Mali K (2021) A morphology-based radiological image segmentation approach for efficient screening of COVID-19. Biomed Signal Process Control. https:\/\/doi.org\/10.1016\/j.bspc.2021.102800","journal-title":"Biomed Signal Process Control"},{"key":"11088_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115069","author":"S Chakraborty","year":"2021","unstructured":"Chakraborty S, Mali K (2021) SUFMACS: a machine learning-based robust image segmentation framework for covid-19 radiological image interpretation. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2021.115069","journal-title":"Expert Syst Appl"},{"key":"11088_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.114142","author":"S Chakraborty","year":"2020","unstructured":"Chakraborty S, Mali K (2020) SuFMoFPA: a superpixel and meta-heuristic based fuzzy image segmentation approach to explicate COVID-19 radiological images. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2020.114142","journal-title":"Expert Syst Appl"},{"key":"11088_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106800","volume":"97","author":"S Chakraborty","year":"2020","unstructured":"Chakraborty S, Mali K (2020) Fuzzy Electromagnetism Optimization (FEMO) and its application in biomedical image segmentation. Appl Soft Comput 97:106800. https:\/\/doi.org\/10.1016\/j.asoc.2020.106800","journal-title":"Appl Soft Comput"},{"key":"11088_CR33","doi-asserted-by":"publisher","first-page":"8527","DOI":"10.1016\/j.eswa.2010.05.023","volume":"37","author":"P Melin","year":"2010","unstructured":"Melin P, Mendoza O, Castillo O (2010) An improved method for edge detection based on interval type-2 fuzzy logic. Expert Syst Appl 37:8527\u20138535. https:\/\/doi.org\/10.1016\/j.eswa.2010.05.023","journal-title":"Expert Syst Appl"},{"key":"11088_CR34","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1109\/MCI.2007.357193","volume":"2","author":"FCH Rhee","year":"2007","unstructured":"Rhee FCH (2007) Uncertain fuzzy clustering: Insights and recommendations. IEEE Comput Intell Mag 2:44\u201356","journal-title":"IEEE Comput Intell Mag"},{"key":"11088_CR35","doi-asserted-by":"crossref","unstructured":"Naz S, Majeed H, Irshad H (2010) Image segmentation using fuzzy clustering: A survey. In: Proceedings of 6th international conference on emerging technologies. ICET 2010, pp 181\u2013186","DOI":"10.1109\/ICET.2010.5638492"},{"key":"11088_CR36","doi-asserted-by":"crossref","unstructured":"Nayak J, Naik B, Behera HS (2015) Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014. In: Smart innovation, systems and technologies. Springer Science and Business Media Deutschland GmbH, pp 133\u2013149","DOI":"10.1007\/978-81-322-2208-8_14"},{"key":"11088_CR37","doi-asserted-by":"crossref","unstructured":"Mange D, Stauffer A, Petraglio E, Tempesti G (2004) Artificial cell division. In: BioSystems. Elsevier, pp 157\u2013167","DOI":"10.1016\/j.biosystems.2004.05.010"},{"key":"11088_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/J.BSPC.2021.103324","volume":"72","author":"S Chakraborty","year":"2022","unstructured":"Chakraborty S, Mali K (2022) Biomedical image segmentation using fuzzy multilevel soft thresholding system coupled modified cuckoo search. Biomed Signal Process Control 72:103324. https:\/\/doi.org\/10.1016\/J.BSPC.2021.103324","journal-title":"Biomed Signal Process Control"},{"key":"11088_CR39","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2021.3097806","author":"W Ding","year":"2021","unstructured":"Ding W, Chakraborty S, Mali K et al (2021) An unsupervised fuzzy clustering approach for early screening of COVID-19 from radiological images. IEEE Trans Fuzzy Syst. https:\/\/doi.org\/10.1109\/TFUZZ.2021.3097806","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"11088_CR40","unstructured":"Rhee FCH, Hwang C (2001) A type-2 fuzzy C-means clustering algorithm. In: Proceedings joint 9th IFSA world congress and 20th NAFIPS international conference (Cat. No. 01TH8569). IEEE, pp 1926\u20131929"},{"key":"11088_CR41","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1166\/jamr.2015.1245","volume":"10","author":"S Hore","year":"2015","unstructured":"Hore S, Chakroborty S, Ashour AS et al (2015) Finding contours of hippocampus brain cell using microscopic image analysis. J Adv Microsc Res 10:93\u2013103. https:\/\/doi.org\/10.1166\/jamr.2015.1245","journal-title":"J Adv Microsc Res"},{"key":"11088_CR42","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1109\/TPAMI.1979.4766909","volume":"1","author":"DL Davies","year":"1979","unstructured":"Davies DL, Bouldin DW (1979) A Cluster Separation Measure. IEEE Trans Pattern Anal Mach Intell PAMI 1:224\u2013227. https:\/\/doi.org\/10.1109\/TPAMI.1979.4766909","journal-title":"IEEE Trans Pattern Anal Mach Intell PAMI"},{"key":"11088_CR43","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1109\/34.85677","volume":"13","author":"XL Xie","year":"1991","unstructured":"Xie XL, Beni G (1991) A validity measure for fuzzy clustering. IEEE Trans Pattern Anal Mach Intell 13:841\u2013847. https:\/\/doi.org\/10.1109\/34.85677","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"11088_CR44","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1080\/01969727408546059","volume":"4","author":"JC Dunn","year":"1974","unstructured":"Dunn JC (1974) Well-separated clusters and optimal fuzzy partitions. J Cybern 4:95\u2013104. https:\/\/doi.org\/10.1080\/01969727408546059","journal-title":"J Cybern"},{"key":"11088_CR45","doi-asserted-by":"publisher","first-page":"2269","DOI":"10.1080\/01431160050029567","volume":"21","author":"SK Pal","year":"2000","unstructured":"Pal SK, Ghosh A, Shankar BU (2000) Segmentation of remotely sensed images with fuzzy thresholding, and quantitative evaluation. Int J Rem Sens 21:2269\u20132300. https:\/\/doi.org\/10.1080\/01431160050029567","journal-title":"Int J Rem Sens"},{"key":"11088_CR46","unstructured":"MedPix Case. https:\/\/medpix.nlm.nih.gov\/case?id=8bd669b5-6e86-4e5a-b2fa-fad020f6cc86&quiz=t. Accessed 11 June 2020"},{"key":"11088_CR47","unstructured":"MedPix Case - Acute Diverticulitis. https:\/\/medpix.nlm.nih.gov\/case?id=889062ec-d5dd-463f-80f2-271a79fbc47f. Accessed 11 June 2020"},{"key":"11088_CR48","unstructured":"MedPix Case - acute infarct. https:\/\/medpix.nlm.nih.gov\/case?id=1a8c19f9-0059-4398-b043-8e8553eddbf3. Accessed 11 June 2020"},{"key":"11088_CR49","unstructured":"MedPix Case - Acute ischemic stroke. https:\/\/medpix.nlm.nih.gov\/case?id=a526b3b3-d307-431a-b40f-bdc68c8bb0b7. Accessed 11 June 2020"},{"key":"11088_CR50","unstructured":"MedPix Case - Acute Myocarditis. https:\/\/medpix.nlm.nih.gov\/case?id=8678a4f4-a0c8-424e-af67-0982c65ba655. Accessed 11 June 2020"},{"key":"11088_CR51","unstructured":"MedPix Case - Acute Basilar Occlusion. https:\/\/medpix.nlm.nih.gov\/case?id=4ebda79a-1ced-4bcb-907d-79be00eb335a. Accessed 11 June 2020"},{"key":"11088_CR52","unstructured":"MedPix Case - Acute Chest Syndrome - Sickle Cell Anemia. https:\/\/medpix.nlm.nih.gov\/case?id=d12fd177-82fe-45e5-b6d3-afebbabe6dc0. Accessed 11 June 2020"},{"key":"11088_CR53","unstructured":"MedPix Case - ACTH-secreting pituitary microadenoma. https:\/\/medpix.nlm.nih.gov\/case?id=2040fcb9-4946-4902-b2e7-f90958650099. Accessed 11 June 2020"},{"key":"11088_CR54","unstructured":"MedPix Case - Alzheimer\u2019s disease (FDG PET pattern, and history). https:\/\/medpix.nlm.nih.gov\/case?id=0696442f-28c1-4bfb-83a0-8e7543b7f1af. Accessed 11 June 2020"},{"key":"11088_CR55","unstructured":"MedPix Case - Airway foreign body \u2013 right bronchus intermedius. https:\/\/medpix.nlm.nih.gov\/case?id=13705556-922b-456c-bc7a-db93bc6c272c. Accessed 11 Jun 2020"},{"key":"11088_CR56","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1023\/A:1024653810491","volume":"14","author":"HZ Jia","year":"2003","unstructured":"Jia HZ, Nee AYC, Fuh JYH, Zhang YF (2003) A modified genetic algorithm for distributed scheduling problems. J Intell Manuf 14:351\u2013362. https:\/\/doi.org\/10.1023\/A:1024653810491","journal-title":"J Intell Manuf"},{"key":"11088_CR57","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1016\/j.cie.2011.10.001","volume":"62","author":"BF Moghaddam","year":"2012","unstructured":"Moghaddam BF, Ruiz R, Sadjadi SJ (2012) Vehicle routing problem with uncertain demands: An advanced particle swarm algorithm. Comput Ind Eng 62:306\u2013317. https:\/\/doi.org\/10.1016\/j.cie.2011.10.001","journal-title":"Comput Ind Eng"},{"key":"11088_CR58","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1504\/IJBIC.2016.078666","volume":"8","author":"X Cai","year":"2016","unstructured":"Cai X, Gao XZ, Xue Y (2016) Improved bat algorithm with optimal forage strategy and random disturbance strategy. Int J Bio-Inspired Comput 8:205\u2013214. https:\/\/doi.org\/10.1504\/IJBIC.2016.078666","journal-title":"Int J Bio-Inspired Comput"},{"key":"11088_CR59","doi-asserted-by":"publisher","DOI":"10.1002\/jemt.22900","author":"S Chakraborty","year":"2017","unstructured":"Chakraborty S, Chatterjee S, Dey N et al (2017) Modified cuckoo search algorithm in microscopic image segmentation of hippocampus. Microsc Res Tech. https:\/\/doi.org\/10.1002\/jemt.22900","journal-title":"Microsc Res Tech"},{"key":"11088_CR60","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/4235.771163","volume":"3","author":"X Yao","year":"1999","unstructured":"Yao X, Liu Y, Lin G (1999) Evolutionary programming made faster. IEEE Trans Evol Comput 3:82\u2013102. https:\/\/doi.org\/10.1109\/4235.771163","journal-title":"IEEE Trans Evol Comput"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-022-11088-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11063-022-11088-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-022-11088-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T16:55:58Z","timestamp":1690822558000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11063-022-11088-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,15]]},"references-count":60,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["11088"],"URL":"https:\/\/doi.org\/10.1007\/s11063-022-11088-x","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2022,11,15]]},"assertion":[{"value":"30 October 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 November 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}