{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T23:46:58Z","timestamp":1782949618043,"version":"3.54.5"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031936968","type":"print"},{"value":"9783031936975","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-031-93697-5_28","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T13:48:30Z","timestamp":1753278510000},"page":"393-406","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["RWAEFA: Random Walk-Based Artificial Electric Field Optimization Algorithm - An Application Towards Feature Selection for\u00a0Cytology Image Classification"],"prefix":"10.1007","author":[{"given":"Subhradeep","family":"Ghosh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soumyajyoti","family":"Dey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soumya","family":"Nasipuri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nibaran","family":"Das","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"28_CR1","doi-asserted-by":"publisher","first-page":"26766","DOI":"10.1109\/ACCESS.2021.3056407","volume":"9","author":"P Agrawal","year":"2021","unstructured":"Agrawal, P., Abutarboush, H.F., Ganesh, T., Mohamed, A.W.: Metaheuristic algorithms on feature selection: a survey of one decade of research (2009\u20132019). IEEE Access 9, 26766\u201326791 (2021)","journal-title":"IEEE Access"},{"issue":"5","key":"28_CR2","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1007\/s42979-021-00741-2","volume":"2","author":"H Basak","year":"2021","unstructured":"Basak, H., Kundu, R., Chakraborty, S., Das, N.: Cervical cytology classification using PCA and GWO enhanced deep features selection. SN Comput. Sci. 2(5), 369 (2021)","journal-title":"SN Comput. Sci."},{"key":"28_CR3","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1016\/j.ins.2017.02.051","volume":"399","author":"JS Chou","year":"2017","unstructured":"Chou, J.S., Pham, A.D.: Nature-inspired metaheuristic optimization in least squares support vector regression for obtaining bridge scour information. Inf. Sci. 399, 64\u201380 (2017)","journal-title":"Inf. Sci."},{"issue":"10167","key":"28_CR4","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/S0140-6736(18)32470-X","volume":"393","author":"PA Cohen","year":"2019","unstructured":"Cohen, P.A., Jhingran, A., Oaknin, A., Denny, L.: Cervical cancer. The Lancet 393(10167), 169\u2013182 (2019)","journal-title":"The Lancet"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"issue":"13","key":"28_CR6","doi-asserted-by":"publisher","DOI":"10.1002\/tal.1777","volume":"29","author":"P Ghannadi","year":"2020","unstructured":"Ghannadi, P., Kourehli, S.S.: Multiverse optimizer for structural damage detection: Numerical study and experimental validation. Struct. Design Tall Spec. Build. 29(13), e1777 (2020)","journal-title":"Struct. Design Tall Spec. Build."},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Haryanto, T., Sitanggang, I.S., Agmalaro, M.A., Rulaningtyas, R.: The utilization of padding scheme on convolutional neural network for cervical cell images classification. In: 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM), pp. 34\u201338. IEEE (2020)","DOI":"10.1109\/CENIM51130.2020.9297895"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"28_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2020.105589","volume":"30","author":"E Hussain","year":"2020","unstructured":"Hussain, E., Mahanta, L.B., Borah, H., Das, C.R.: Liquid based-cytology pap smear dataset for automated multi-class diagnosis of pre-cancerous and cervical cancer lesions. Data Brief 30, 105589 (2020)","journal-title":"Data Brief"},{"key":"28_CR10","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1007\/s13198-014-0286-6","volume":"9","author":"SS Jadon","year":"2018","unstructured":"Jadon, S.S., Bansal, J.C., Tiwari, R., Sharma, H.: Artificial bee colony algorithm with global and local neighborhoods. Int. J. Syst. Assur. Eng. Manage. 9, 589\u2013601 (2018)","journal-title":"Int. J. Syst. Assur. Eng. Manage."},{"issue":"17","key":"28_CR11","doi-asserted-by":"publisher","first-page":"2914","DOI":"10.1016\/j.neucom.2011.03.034","volume":"74","author":"MM Kabir","year":"2011","unstructured":"Kabir, M.M., Shahjahan, M., Murase, K.: A new local search based hybrid genetic algorithm for feature selection. Neurocomputing 74(17), 2914\u20132928 (2011)","journal-title":"Neurocomputing"},{"key":"28_CR12","doi-asserted-by":"crossref","unstructured":"Li, C., et al.: Transfer learning based classification of cervical cancer immunohistochemistry images. In: Proceedings of the Third International Symposium on Image Computing and Digital Medicine, pp. 102\u2013106 (2019)","DOI":"10.1145\/3364836.3364857"},{"key":"28_CR13","unstructured":"Liang, J.J., Qu, B.Y., Suganthan, P.N.: Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective real-parameter numerical optimization. Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore 635(2) (2013)"},{"issue":"1","key":"28_CR14","doi-asserted-by":"publisher","first-page":"14538","DOI":"10.1038\/s41598-021-93783-8","volume":"11","author":"A Manna","year":"2021","unstructured":"Manna, A., Kundu, R., Kaplun, D., Sinitca, A., Sarkar, R.: A fuzzy rank-based ensemble of CNN models for classification of cervical cytology. Sci. Rep. 11(1), 14538 (2021)","journal-title":"Sci. Rep."},{"key":"28_CR15","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/j.asoc.2015.09.045","volume":"40","author":"SA Medjahed","year":"2016","unstructured":"Medjahed, S.A., Saadi, T.A., Benyettou, A., Ouali, M.: Gray wolf optimizer for hyperspectral band selection. Appl. Soft Comput. 40, 178\u2013186 (2016)","journal-title":"Appl. Soft Comput."},{"issue":"3","key":"28_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3447238","volume":"54","author":"S Mitra","year":"2021","unstructured":"Mitra, S., Das, N., Dey, S., Chakraborty, S., Nasipuri, M., Naskar, M.K.: Cytology image analysis techniques toward automation: systematically revisited. ACM Comput. Surv.(CSUR) 54(3), 1\u201341 (2021)","journal-title":"ACM Comput. Surv.(CSUR)"},{"issue":"5","key":"28_CR17","doi-asserted-by":"publisher","first-page":"3714","DOI":"10.1016\/j.eswa.2009.11.054","volume":"37","author":"H Modares","year":"2010","unstructured":"Modares, H., Alfi, A., Fateh, M.M.: Parameter identification of chaotic dynamic systems through an improved particle swarm optimization. Expert Syst. Appl. 37(5), 3714\u20133720 (2010)","journal-title":"Expert Syst. Appl."},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Plissiti, M.E., Dimitrakopoulos, P., Sfikas, G., Nikou, C., Krikoni, O., Charchanti, A.: Sipakmed: a new dataset for feature and image based classification of normal and pathological cervical cells in pap smear images. In: 2018 25th IEEE International Conference on Image Processing (ICIP), pp. 3144\u20133148. IEEE (2018)","DOI":"10.1109\/ICIP.2018.8451588"},{"issue":"13","key":"28_CR19","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","volume":"179","author":"E Rashedi","year":"2009","unstructured":"Rashedi, E., Nezamabadi-Pour, H., Saryazdi, S.: GSA: a gravitational search algorithm. Inf. Sci. 179(13), 2232\u20132248 (2009)","journal-title":"Inf. Sci."},{"key":"28_CR20","doi-asserted-by":"crossref","unstructured":"Rojas, R., Rojas, R.: The backpropagation algorithm. Neural networks: a systematic introduction, pp. 149\u2013182 (1996)","DOI":"10.1007\/978-3-642-61068-4_7"},{"issue":"3","key":"28_CR21","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., et al.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vision 115(3), 211\u2013252 (2015). https:\/\/doi.org\/10.1007\/s11263-015-0816-y","journal-title":"Int. J. Comput. Vision"},{"key":"28_CR22","unstructured":"Schutte, J.F.: The particle swarm optimization algorithm. Structural Optimization (2005)"},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Shehadeh, H.A., Ahmedy, I., Idris, M.Y.I.: Empirical study of sperm swarm optimization algorithm. In: Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2, pp. 1082\u20131104. Springer (2019)","DOI":"10.1007\/978-3-030-01057-7_80"},{"key":"28_CR24","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1007\/s00500-016-2474-6","volume":"22","author":"D Wang","year":"2018","unstructured":"Wang, D., Tan, D., Liu, L.: Particle swarm optimization algorithm: an overview. Soft. Comput. 22, 387\u2013408 (2018)","journal-title":"Soft. Comput."},{"issue":"5","key":"28_CR25","doi-asserted-by":"publisher","first-page":"1800","DOI":"10.3390\/app10051800","volume":"10","author":"KP Win","year":"2020","unstructured":"Win, K.P., Kitjaidure, Y., Hamamoto, K., Myo Aung, T.: Computer-assisted screening for cervical cancer using digital image processing of pap smear images. Appl. Sci. 10(5), 1800 (2020)","journal-title":"Appl. Sci."},{"key":"28_CR26","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.swevo.2019.03.013","volume":"48","author":"A Yadav","year":"2019","unstructured":"Yadav, A., et al.: AEFA: artificial electric field algorithm for global optimization. Swarm Evol. Comput. 48, 93\u2013108 (2019)","journal-title":"Swarm Evol. Comput."}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-93697-5_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T23:23:15Z","timestamp":1782948195000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-93697-5_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,24]]},"ISBN":["9783031936968","9783031936975"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-93697-5_28","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,24]]},"assertion":[{"value":"24 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chennai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cvip2024.iiitdm.ac.in\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}