{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T12:03:44Z","timestamp":1774872224434,"version":"3.50.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2018,9,22]],"date-time":"2018-09-22T00:00:00Z","timestamp":1537574400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2019,6]]},"DOI":"10.1007\/s00521-018-3711-y","type":"journal-article","created":{"date-parts":[[2018,9,22]],"date-time":"2018-09-22T08:15:14Z","timestamp":1537604114000},"page":"1805-1822","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Improving the performance of convolutional neural network for skin image classification using the response of image analysis filters"],"prefix":"10.1007","volume":"31","author":[{"given":"S. V.","family":"Georgakopoulos","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K.","family":"Kottari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K.","family":"Delibasis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. P.","family":"Plagianakos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2860-399X","authenticated-orcid":false,"given":"I.","family":"Maglogiannis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,22]]},"reference":[{"issue":"4","key":"3711_CR1","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1016\/j.mayocp.2012.01.010","volume":"87","author":"KB Reed","year":"2012","unstructured":"Reed KB, Brewer JD, Lohse CM, Bringe KE, Pruit CN, Gibson LE (2012) Increasing incidence of melanoma among young adults: an epidemiological study in Olmsted County, Minnesota. Mayo Clin Proc 87(4):328\u2013334","journal-title":"Mayo Clin Proc"},{"issue":"3","key":"3711_CR2","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1001\/archdermatol.2010.4","volume":"146","author":"RS Stern","year":"2010","unstructured":"Stern RS (2010) Prevalence of a history of skin cancer in 2007: results of an incidence-based model. Arch Dermatol 146(3):279\u2013282","journal-title":"Arch Dermatol"},{"issue":"3","key":"3711_CR3","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1001\/archdermatol.2010.19","volume":"146","author":"HW Rogers","year":"2010","unstructured":"Rogers HW, Weinstock MA, Harris AR et al (2010) Incidence estimate of nonmelanoma skin cancer in the United States, 2006. Arch Dermatol 146(3):283\u2013287","journal-title":"Arch Dermatol"},{"key":"3711_CR4","unstructured":"American Cancer Society (2015) Cancer facts and figures. \n                    http:\/\/www.cancer.org\/research\/cancerfactsstatistics\/cancerfactsfigures2015\/\n                    \n                  . Accessed 12 May 2015"},{"issue":"5","key":"3711_CR5","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1109\/TITB.2009.2017529","volume":"13","author":"I Maglogiannis","year":"2009","unstructured":"Maglogiannis I, Doukas CN (2009) Overview of advanced computer vision systems for skin lesions characterization. IEEE Trans Inf Technol Biomed 13(5):721\u2013733","journal-title":"IEEE Trans Inf Technol Biomed"},{"issue":"1","key":"3711_CR6","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1111\/j.1529-8019.2005.00054.x","volume":"19","author":"SW Menzies","year":"2006","unstructured":"Menzies SW (2006) Cutaneous melanoma: making a clinical diagnosis, present and future. Dermatol Ther 19(1):32\u201339","journal-title":"Dermatol Ther"},{"issue":"2","key":"3711_CR7","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.artmed.2012.08.002","volume":"56","author":"K Korotkov","year":"2012","unstructured":"Korotkov K, Garcia R (2012) Computerized analysis of pigmented skin lesions: a review. Artif Intell Med 56(2):69\u201390","journal-title":"Artif Intell Med"},{"issue":"2","key":"3711_CR8","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.cmpb.2014.12.001","volume":"118","author":"I Maglogiannis","year":"2015","unstructured":"Maglogiannis I, Delibasis K (2015) Enhancing classification accuracy utilizing globules and dots features in digital dermoscopy. Comput Methods Progr Biomed 118(2):124\u2013133 (ISSN 0169-2607)","journal-title":"Comput Methods Progr Biomed"},{"issue":"1","key":"3711_CR9","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1006\/jbin.2001.1004","volume":"34","author":"S Dreiseitl","year":"2001","unstructured":"Dreiseitl S, Ohno-Machado L, Kittler H, Vinterbo S, Billhardt H, Binder M (2001) A comparison of machine learning methods for the diagnosis of pigmented skin lesions. J Biomed Inf 34(1):28\u201336","journal-title":"J Biomed Inf"},{"key":"3711_CR10","doi-asserted-by":"crossref","unstructured":"Maglogiannis I, Zafiropoulos E (2004) Utilizing support vector machines for the characterization of digital medical images. BMC Med Inf Decis Mak 4(4)","DOI":"10.1186\/1472-6947-4-4"},{"key":"3711_CR11","doi-asserted-by":"crossref","unstructured":"Maragoudakis M, Maglogiannis I (2010) Skin lesion diagnosis from images using novel ensemble classification techniques. In: Information technology and applications in biomedicine (ITAB), 2010 10th IEEE international conference on IEEE, pp 1\u20135","DOI":"10.1109\/ITAB.2010.5687620"},{"key":"3711_CR12","unstructured":"Codella N, Gutman D, Celebi ME, Helba B, Marchetti MA, Dusza S, Kalloo A, Liopyris K, Mishra N, Kittler H, Halpern A (2017) Skin lesion analysis toward melanoma detection: a challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (ISIC). arXiv: 1710.05006"},{"issue":"11","key":"3711_CR13","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K, Lucchi A, Fua P, S\u00fcsstrunk S (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132282","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3711_CR14","doi-asserted-by":"crossref","unstructured":"Delibasis K, Kottari K, Maglogiannis I (2015) Automated detection of streaks in dermoscopy images. In: IFIP international conference on artificial intelligence applications and innovations. Springer, Berlin, pp 45\u201360","DOI":"10.1007\/978-3-319-23868-5_4"},{"issue":"2","key":"3711_CR15","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.cmpb.2014.12.001","volume":"118","author":"I Maglogiannis","year":"2015","unstructured":"Maglogiannis I, Delibasis KK (2015) Enhancing classification accuracy utilizing globules and dots features in digital dermoscopy. Comput Methods Progr Biomed 118(2):124\u2013133","journal-title":"Comput Methods Progr Biomed"},{"key":"3711_CR16","doi-asserted-by":"crossref","unstructured":"Sadeghi M, Lee TK, McLean D, Harvey Lui, Atkins MS (2012) Oriented pattern analysis for streak detection in dermoscopy images. In: Ayache N et al (eds) MICCAI 2012, Part I, LNCS 7510, pp 298\u2013306","DOI":"10.1007\/978-3-642-33415-3_37"},{"issue":"5","key":"3711_CR17","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1109\/TMI.2013.2239307","volume":"32","author":"M Sadeghi","year":"2013","unstructured":"Sadeghi M, Lee TK, McLean D, Lui H, Atkins MS (2013) Detection and analysis of irregular streaks in dermoscopic images of skin lesions. IEEE Trans Med Imaging 32(5):849\u2013861","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"3711_CR18","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.1109\/TMI.2016.2535302","volume":"35","author":"N Tajbakhsh","year":"2016","unstructured":"Tajbakhsh N, Shin JY, Gurudu SR, Hurst RT, Kendall CB, Gotway MB, Liang J (2016) Convolutional neural networks for medical image analysis: Full training or fine tuning? IEEE Trans Med Imaging 35(5):1299\u20131312","journal-title":"IEEE Trans Med Imaging"},{"key":"3711_CR19","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3138-x","author":"X Wang","year":"2017","unstructured":"Wang X, Guo Y, Wang Y, Yu J (2017) Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns. Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-017-3138-x","journal-title":"Neural Comput Appl"},{"key":"3711_CR20","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.neucom.2017.08.071","volume":"280","author":"SV Georgakopoulos","year":"2018","unstructured":"Georgakopoulos SV, Kottari K, Delibasis K, Plagianakos VP, Maglogiannis I (2018) Pose recognition using convolutional neural networks on omni-directional images. Neurocomputing 280:23\u201331","journal-title":"Neurocomputing"},{"key":"3711_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3333-9","author":"\u015e \u00d6zt\u00fcrk","year":"2017","unstructured":"\u00d6zt\u00fcrk \u015e, Akdemir B (2017) A convolutional neural network model for semantic segmentation of mitotic events in microscopy images. Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-017-3333-9","journal-title":"Neural Comput Appl"},{"issue":"7639","key":"3711_CR22","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1038\/nature21056","volume":"542","author":"A Esteva","year":"2017","unstructured":"Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S (2017) Dermatologist-level classification of skin cancer with deep neural networks. Nature 542(7639):115","journal-title":"Nature"},{"issue":"4","key":"3711_CR23","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1109\/TMI.2016.2642839","volume":"36","author":"L Yu","year":"2017","unstructured":"Yu L, Chen H, Dou Q, Qin J, Heng PA (2017) Automated melanoma recognition in dermoscopy images via very deep residual networks. IEEE Trans Med Imaging 36(4):994\u20131004","journal-title":"IEEE Trans Med Imaging"},{"key":"3711_CR24","doi-asserted-by":"crossref","unstructured":"Kawahara J, BenTaieb A, Hamarneh G (2016) Deep features to classify skin lesions. In: Biomedical imaging (ISBI), 2016 IEEE 13th international symposium on IEEE, pp 1397\u20131400","DOI":"10.1109\/ISBI.2016.7493528"},{"issue":"2","key":"3711_CR25","doi-asserted-by":"publisher","first-page":"556","DOI":"10.3390\/s18020556","volume":"18","author":"Y Li","year":"2018","unstructured":"Li Y, Shen L (2018) Skin lesion analysis towards melanoma detection using deep learning network. Sensors 18(2):556","journal-title":"Sensors"},{"key":"3711_CR26","doi-asserted-by":"publisher","first-page":"907","DOI":"10.3390\/rs9090907","volume":"9","author":"Z Huang","year":"2017","unstructured":"Huang Z, Pan Z, Lei B (2017) Transfer learning with deep convolutional neural network for SAR target classification with limited labeled data. Remote Sens 9:907","journal-title":"Remote Sens"},{"key":"3711_CR27","volume-title":"Neural networks: a comprehensive foundation","author":"S Haykin","year":"1998","unstructured":"Haykin S (1998) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall PTR, Upper Saddle River","edition":"2"},{"issue":"11","key":"3711_CR28","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11):2278\u20132324","journal-title":"Proc IEEE"},{"key":"3711_CR29","volume-title":"In on-line learning in neural networks","author":"L Bottou","year":"1998","unstructured":"Bottou L (1998) On-line learning and stochastic approximations. In: Saad D (ed) In on-line learning in neural networks. Cambridge University Press, UK"},{"issue":"2","key":"3711_CR30","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91\u2013110","journal-title":"Int J Comput Vis"},{"issue":"43","key":"3711_CR31","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/s11263-005-3848-x","volume":"65","author":"K Mikolajczyk","year":"2005","unstructured":"Mikolajczyk K, Tuytelaars T, Schmid C, Zisserman A, Matas J, Schaffalitzky F, Kadir T Van, Gool L (2005) A comparison of affine region detectors. Int J Comput Vis 65(43):43\u201372","journal-title":"Int J Comput Vis"},{"issue":"3","key":"3711_CR32","first-page":"177","volume":"3","author":"T Tuytelaars","year":"2007","unstructured":"Tuytelaars T, Mikolajczy K (2007) kLocal invariant feature detectors: a survey. Comput Gr Vis 3(3):177\u2013280","journal-title":"Comput Gr Vis"},{"key":"3711_CR33","doi-asserted-by":"crossref","unstructured":"Frangi A, Niessen WJ, Vincken KL, Viergever MA (1998) Multiscale vessel enhancement filtering. In: Proceedings of the 1st international conference of medical image computing and computer-assisted intervention (MICCAI 1998), pp 130\u2013137","DOI":"10.1007\/BFb0056195"},{"issue":"2","key":"3711_CR34","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1006\/cviu.2000.0866","volume":"80","author":"K Krissian","year":"2000","unstructured":"Krissian K, Malandain G, Ayache N, Vaillant R, Trousset Y (2000) Model based detection of tubular structures in 3d images. Comput Vis Image Underst 80(2):130\u2013171","journal-title":"Comput Vis Image Underst"},{"issue":"2","key":"3711_CR35","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1023\/A:1008097225773","volume":"30","author":"T Lindeberg","year":"1998","unstructured":"Lindeberg T (1998) Edge detection and ridge detection with automatic scale selection. Int J Comput Vis 30(2):117\u2013154","journal-title":"Int J Comput Vis"},{"issue":"7","key":"3711_CR36","doi-asserted-by":"publisher","first-page":"1160","DOI":"10.1364\/JOSAA.2.001160","volume":"2","author":"JG Daugman","year":"1985","unstructured":"Daugman JG et al (1985) Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. Opt Soc Am J A Opt Image Sci 2(7):1160\u20131169","journal-title":"Opt Soc Am J A Opt Image Sci"},{"issue":"12","key":"3711_CR37","doi-asserted-by":"publisher","first-page":"2005","DOI":"10.1016\/S0031-3203(96)00047-7","volume":"29","author":"TP Weldon","year":"1996","unstructured":"Weldon TP, Higgins WE, Dunn DF (1996) Efficient Gabor filter design for texture segmentation. Pattern Recogn 29(12):2005\u20132015","journal-title":"Pattern Recogn"},{"issue":"5","key":"3711_CR38","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1016\/j.patrec.2007.12.001","volume":"29","author":"M Li","year":"2008","unstructured":"Li M, Staunton RC (2008) Optimum Gabor filter design and local binary patterns for texture segmentation. Pattern Recogn Lett 29(5):664\u2013672","journal-title":"Pattern Recogn Lett"},{"key":"3711_CR39","first-page":"1097","volume-title":"Advances in neural information processing systems","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Pereira F, Burges CJC, Bottou L, Weinberger KQ (eds) Advances in neural information processing systems, vol 25. Curran Associates Inc., NewYork, pp 1097\u20131105"},{"key":"3711_CR40","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) ImageNet: a large-scale hierarchical image database. In: CVPR09","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"3711_CR41","doi-asserted-by":"crossref","unstructured":"Georgakopoulos SV, Iakovidis DK, Vasilakakis M, Plagianakos VP, Koulaouzidis A (2016) Weakly-supervised convolutional learning for detection of inflammatory gastrointestinal lesions. In: 2016 IEEE international conference on imaging systems and techniques (IST), pp 510\u2013514","DOI":"10.1109\/IST.2016.7738279"},{"issue":"3","key":"3711_CR42","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1038\/nrgastro.2015.13","volume":"12","author":"DK Iakovidis","year":"2015","unstructured":"Iakovidis DK, Koulaouzidis A (2015) Software for enhanced video capsule endoscopy: challenges for essential progress. Nat Rev Gastroenterol Hepatol 12(3):172\u2013186","journal-title":"Nat Rev Gastroenterol Hepatol"},{"key":"3711_CR43","first-page":"3320","volume":"27","author":"J Yosinski","year":"2014","unstructured":"Yosinski J, Clune J, Bengio Y, Lipson H (2014) How transferable are features in deep neural networks? Adv Neural Inf Process Syst 27:3320\u20133328","journal-title":"Adv Neural Inf Process Syst"},{"issue":"11","key":"3711_CR44","doi-asserted-by":"publisher","first-page":"1958","DOI":"10.1109\/TPAMI.2008.128","volume":"30","author":"A Torralba","year":"2008","unstructured":"Torralba A, Fergus R, Freeman WT (2008) 80 million tiny images: a large data set for nonparametric object and scene recognition. IEEE Trans Pattern Anal Mach Intell 30(11):1958\u20131970","journal-title":"IEEE Trans Pattern Anal Mach Intell"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3711-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-018-3711-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3711-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,21]],"date-time":"2019-09-21T19:12:26Z","timestamp":1569093146000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-018-3711-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,22]]},"references-count":44,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2019,6]]}},"alternative-id":["3711"],"URL":"https:\/\/doi.org\/10.1007\/s00521-018-3711-y","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,22]]},"assertion":[{"value":"11 January 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 September 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}