{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T03:26:36Z","timestamp":1784777196442,"version":"3.55.0"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T00:00:00Z","timestamp":1653868800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T00:00:00Z","timestamp":1653868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001230","name":"Macquarie University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001230","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Evol. Intel."],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Adult content images have a detrimental effect on Internet users, a significant number of whom are minors. Therefore, it is essential to control and detecting adult content images using multimedia processing and computer vision techniques. Previous studies have typically focused on manual-engineered visual features that may be difficult to detect and analyze. This paper presents a new model that employs deep convolutional neural networks within a Gaussian-Bernoulli limited-time, for adult content image recognition of a wide variety in a precise and effective manner. There are various layers within Convolutional Neural Networks for feature extraction and classification. Gaussian-Bernoulli limited-time was used for feature extraction to describe the images, and these features were summarized using the Boltzmann machine limited in the feature summary phase. The benefit of such an approach is convenience in carrying out feature extraction. Additionally, when tested on the most modern criterion dataset, this finding is believed to be more precise compared to other state-of-the-art approaches. The results obtained prove that the proposed approach leads to a higher efficiency.<\/jats:p>","DOI":"10.1007\/s12065-022-00729-8","type":"journal-article","created":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T07:02:55Z","timestamp":1653894175000},"page":"1185-1194","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Adult content image recognition by Boltzmann machine limited and deep learning"],"prefix":"10.1007","volume":"16","author":[{"given":"Sasan","family":"Karamizadeh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2958-6901","authenticated-orcid":false,"given":"Saman","family":"Shojae Chaeikar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alireza","family":"Jolfaei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,5,30]]},"reference":[{"issue":"1","key":"729_CR1","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1007\/s11042-016-4273-6","volume":"77","author":"S Shojae Chaeikar","year":"2018","unstructured":"Shojae Chaeikar S, Zamani M, Abdul Manaf AB, Zeki AM (2018) PSW statistical LSB image steganalysis. Multimed Tools Appl 77(1):805\u2013835","journal-title":"Multimed Tools Appl"},{"issue":"2","key":"729_CR2","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1007\/s10462-018-9664-9","volume":"52","author":"S Naji","year":"2019","unstructured":"Naji S, Jalab HA, Kareem SA (2019) A survey on skin detection in colored images. Artif Intell Rev 52(2):1041\u20131087","journal-title":"Artif Intell Rev"},{"key":"729_CR3","doi-asserted-by":"crossref","unstructured":"Sharma R (2020) Using transfer learning to classify pornographic images. In\u00a02020 6th conference on data science and machine learning applications (CDMA), pp 43\u201346. IEEE","DOI":"10.1109\/CDMA47397.2020.00013"},{"issue":"70","key":"729_CR4","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/j.image.2018.10.004","volume":"1","author":"SS Chaeikar","year":"2019","unstructured":"Chaeikar SS, Ahmadi A (2019) Ensemble SW image steganalysis: a low dimension method for LSBR detection. Signal Process Image Commun 1(70):233\u2013245","journal-title":"Signal Process Image Commun"},{"key":"729_CR5","doi-asserted-by":"crossref","unstructured":"Thakkar S, Joshi MV (2017) Classification of human actions using 3-d convolutional neural networks: a hierarchical approach. In:\u00a0National conference on computer vision, pattern recognition, image processing, and graphics, pp 14\u201323. Springer, Singapore","DOI":"10.1007\/978-981-13-0020-2_2"},{"issue":"4","key":"729_CR6","doi-asserted-by":"publisher","first-page":"615","DOI":"10.3390\/electronics9040615","volume":"9","author":"S Shojae Chaeikar","year":"2020","unstructured":"Shojae Chaeikar S, Manaf AA, Alarood AA, Zamani M (2020) PFW: polygonal fuzzy weighted\u2014an SVM kernel for the classification of overlapping data groups. Electronics 9(4):615","journal-title":"Electronics"},{"key":"729_CR7","doi-asserted-by":"crossref","unstructured":"Chaeikar SS, Alizadeh M, Tadayon MH, Jolfaei A (2021) An intelligent cryptographic key management model for secure communications in distributed industrial intelligent systems. Int J Intell Syst, 25","DOI":"10.1002\/int.22435"},{"key":"729_CR8","doi-asserted-by":"crossref","unstructured":"Nguyen QH, Tran HL, Nguyen TT, Phan DD, Vu DL (2020) Multi-level detector for pornographic content using CNN models. In: 2020 RIVF international conference on computing and communication technologies (RIVF), pp 1\u20135. IEEE","DOI":"10.1109\/RIVF48685.2020.9140734"},{"key":"729_CR9","doi-asserted-by":"publisher","first-page":"432","DOI":"10.1016\/j.neucom.2017.07.012","volume":"272","author":"J Wehrmann","year":"2018","unstructured":"Wehrmann J, Sim\u00f5es GS, Barros RC, Cavalcante VF (2018) Adult content detection in videos with convolutional and recurrent neural networks. Neurocomputing 272:432\u2013438","journal-title":"Neurocomputing"},{"key":"729_CR10","doi-asserted-by":"crossref","unstructured":"Cifuentes J, Orozco ALS, Villalba LJG (2021) A survey of artificial intelligence strategies for automatic detection of sexually explicit videos.\u00a0Multimed Tools Appl, 1\u201318","DOI":"10.1007\/s11042-021-10628-2"},{"issue":"1","key":"729_CR11","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1515\/comp-2020-0167","volume":"12","author":"SS Chaeikar","year":"2022","unstructured":"Chaeikar SS, Ahmadi A, Karamizadeh S, Chaeikar NS (2022) SIKM \u2013 a smart cryptographic key management framework. Open Comput Sci 12(1):17\u201326","journal-title":"Open Comput Sci"},{"issue":"1","key":"729_CR12","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/s13042-020-01157-9","volume":"12","author":"X Lin","year":"2021","unstructured":"Lin X, Qin F, Peng Y, Shao Y (2021) Fine-grained pornographic image recognition with multiple feature fusion transfer learning. Int J Mach Learn Cybern 12(1):73\u201386","journal-title":"Int J Mach Learn Cybern"},{"key":"729_CR13","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.patrec.2020.09.027","volume":"140","author":"L Wang","year":"2020","unstructured":"Wang L, Zhang J, Wang M, Tian J, Zhuo L (2020) Multilevel fusion of multimodal deep features for porn streamer recognition in live video. Pattern Recogn Lett 140:150\u2013157","journal-title":"Pattern Recogn Lett"},{"key":"729_CR14","doi-asserted-by":"crossref","unstructured":"Cheng G, Li Z, Yao X, Guo L, Wei Z (2017) Remote sensing image scene classification using bag of convolutional features.\u00a0IEEE Geosci Remote Sens Lett, 14(10)","DOI":"10.1109\/LGRS.2017.2731997"},{"key":"729_CR15","doi-asserted-by":"crossref","unstructured":"Vakili N, Krathu W, Laomaneerattanaporn N (2021) Multi-class primary morphology lesions classification using deep convolutional neural network. In:\u00a0The 12th international conference on advances in information technology, pp 1\u20137","DOI":"10.1145\/3468784.3468887"},{"issue":"1","key":"729_CR16","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s11063-020-10238-3","volume":"52","author":"W Xu","year":"2020","unstructured":"Xu W, Parvin H, Izadparast H (2020) Deep learning neural network for unconventional images classification. Neural Process Lett 52(1):169\u2013185","journal-title":"Neural Process Lett"},{"issue":"4","key":"729_CR17","first-page":"50","volume":"9","author":"S Karamizadeh","year":"2017","unstructured":"Karamizadeh S, Arabsorkhi A (2017) Enhancement of Illumination scheme for Adult Image Recognition. Int J Inf Commun Technol Res 9(4):50\u201356","journal-title":"Int J Inf Commun Technol Res"},{"key":"729_CR18","doi-asserted-by":"crossref","unstructured":"Karamizadeh S, Arabsorkhi A (2018) Methods of pornography detection. In:\u00a0Proceedings of the 10th international conference on computer modeling and simulation, pp 33\u201338","DOI":"10.1145\/3177457.3177484"},{"key":"729_CR19","unstructured":"Karamizadeh S, Randjbaran E, Javad Rajabi M (2015) A review on techniques of illumination in face recognition.\u00a0Int J Eng Technol Sci,\u00a03(2): 79\u201383"},{"key":"729_CR20","doi-asserted-by":"crossref","unstructured":"de Freitas PV, Busson AJ, Guedes \u00c1L, Colcher S (2020)A deep learning approach to detect pornography videos in educational repositories. In:\u00a0Anais do XXXI Simp\u00f3sio Brasileiro de Inform\u00e1tica na Educa\u00e7\u00e3o, pp 1253\u20131262. SBC","DOI":"10.5753\/cbie.sbie.2020.1253"},{"issue":"41","key":"729_CR21","first-page":"1","volume":"41","author":"S Karamizadeh","year":"2020","unstructured":"Karamizadeh S (2020) New method to improve illumination variations in adult images based on fuzzy deep neural network. J Inf Commun Technol 41(41):1","journal-title":"J Inf Commun Technol"},{"key":"729_CR22","doi-asserted-by":"publisher","first-page":"85284","DOI":"10.1109\/ACCESS.2020.2993227","volume":"8","author":"Y Wan","year":"2020","unstructured":"Wan Y, Yu Z, Wang Y, Li X (2020) Action recognition based on two-stream convolutional networks with long-short-term spatiotemporal features. IEEE Access 8:85284\u201385293","journal-title":"IEEE Access"},{"key":"729_CR23","doi-asserted-by":"crossref","unstructured":"Wehrmann J, Sim\u02dcoes G, Rodrigo B, Paula T, Ruiz D (2016) (deep) learning 445 from frames. In: Proceedings of the Brazilian conference on intelligent system, 2016.","DOI":"10.1109\/BRACIS.2016.012"},{"issue":"2","key":"729_CR24","first-page":"314","volume":"13","author":"S Karamizadeh","year":"2015","unstructured":"Karamizadeh S, Cheraghi SM, Zamani M (2015) Filtering based illumination normalization techniques for face recognition. TELKOMNIKA Indonesian J Electr Eng 13(2):314\u2013320","journal-title":"TELKOMNIKA Indonesian J Electr Eng"},{"issue":"11","key":"729_CR25","doi-asserted-by":"publisher","first-page":"4806","DOI":"10.1109\/TNNLS.2019.2958103","volume":"31","author":"SN Tran","year":"2020","unstructured":"Tran SN, Garcez ADA, Weyde T, Yin J, Zhang Q, Karunanithi M (2020) Sequence classification restricted Boltzmann machines with gated units. IEEE Trans Neural Netw Learn Syst 31(11):4806\u20134815","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"1","key":"729_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13721-019-0207-3","volume":"9","author":"R Javed","year":"2020","unstructured":"Javed R, Rahim MSM, Saba T, Rehman A (2020) A comparative study of features selection for skin lesion detection from dermoscopic images. Netw Model Anal Health Inf Bioinf 9(1):1\u201313","journal-title":"Netw Model Anal Health Inf Bioinf"},{"issue":"5","key":"729_CR27","doi-asserted-by":"publisher","first-page":"11909","DOI":"10.1007\/s10586-017-1510-3","volume":"22","author":"R Balamurali","year":"2019","unstructured":"Balamurali R, Chandrasekar A (2019) Multiple parameter algorithm approach for adult image identification. Clust Comput 22(5):11909\u201311917","journal-title":"Clust Comput"},{"key":"729_CR28","doi-asserted-by":"crossref","unstructured":"Dewi C, Chen RC, Hendry, Hung HT (2021) Experiment improvement of restricted Boltzmann machine methods for image classification.\u00a0Vietnam J Comput Sci, 1\u201316","DOI":"10.1142\/S2196888821500184"},{"key":"729_CR29","doi-asserted-by":"crossref","unstructured":"Aamir M, Nawi N., Wahid F, Zada MSH, Rehman MZ, Zulqarnain, M (2021) Hybrid contractive auto-encoder with restricted Boltzmann machine for multiclass classification.\u00a0Arab J Sci Eng, 1\u201315","DOI":"10.1007\/s13369-021-05674-9"}],"container-title":["Evolutionary Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12065-022-00729-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12065-022-00729-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12065-022-00729-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,11]],"date-time":"2023-07-11T06:12:57Z","timestamp":1689055977000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12065-022-00729-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,30]]},"references-count":29,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["729"],"URL":"https:\/\/doi.org\/10.1007\/s12065-022-00729-8","relation":{},"ISSN":["1864-5909","1864-5917"],"issn-type":[{"value":"1864-5909","type":"print"},{"value":"1864-5917","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,30]]},"assertion":[{"value":"29 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 April 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 May 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}