{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T11:02:57Z","timestamp":1782990177134,"version":"3.54.5"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neural Networks"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.neunet.2026.108715","type":"journal-article","created":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:05:05Z","timestamp":1770739505000},"page":"108715","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Transforming tabular data into images for deep learning models"],"prefix":"10.1016","volume":"199","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1644-0476","authenticated-orcid":false,"given":"Abdullah","family":"Elen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emre","family":"Avu\u00e7lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"10","key":"10.1016\/j.neunet.2026.108715_bib0001","doi-asserted-by":"crossref","first-page":"1533","DOI":"10.1109\/TASLP.2014.2339736","article-title":"Convolutional neural networks for speech recognition","volume":"22","author":"Abdel-Hamid","year":"2014","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"key":"10.1016\/j.neunet.2026.108715_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2022.103836","article-title":"A novel method using Covid-19 dataset and machine learning algorithms for the most accurate diagnosis that can be obtained in medical diagnosis","volume":"77","author":"Avu\u00e7lu","year":"2022","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.neunet.2026.108715_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2022.111702","article-title":"COVID-19 detection using X-ray images and statistical measurements","volume":"201","author":"Avu\u00e7lu","year":"2022","journal-title":"Measurement"},{"key":"10.1016\/j.neunet.2026.108715_bib0004","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.eswa.2019.06.018","article-title":"A recursive general regression neural network (R-GRNN) oracle for classification problems","volume":"135","author":"Bani-Hani","year":"2019","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.neunet.2026.108715_bib0005","series-title":"Proceedings of the IEEE 4th conference on information & communication technology (CICT)","article-title":"Malware dataset generation and evaluation","author":"Borah","year":"2020"},{"key":"10.1016\/j.neunet.2026.108715_bib0006","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1007\/s10994-018-5746-9","article-title":"A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data","volume":"108","author":"Boull\u00e9","year":"2019","journal-title":"Machine Learning"},{"key":"10.1016\/j.neunet.2026.108715_bib0007","doi-asserted-by":"crossref","first-page":"113100","DOI":"10.1109\/ACCESS.2023.3323927","article-title":"Tabular-to-image transformations for the classification of anonymous network traffic using deep residual networks","volume":"11","author":"Briner","year":"2023","journal-title":"IEEE Access"},{"issue":"2","key":"10.1016\/j.neunet.2026.108715_bib0008","first-page":"307","article-title":"Identification of rice varieties using machine learning algorithms","volume":"28","author":"Cinar","year":"2022","journal-title":"Journal of Agricultural Sciences"},{"key":"10.1016\/j.neunet.2026.108715_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.datak.2022.102075","article-title":"Enhancing classification capacity of CNN models with deep feature selection and fusion: A case study on maize seed classification","volume":"141","author":"D\u00f6nmez","year":"2022","journal-title":"Data & Knowledge Engineering"},{"issue":"23","key":"10.1016\/j.neunet.2026.108715_bib0010","doi-asserted-by":"crossref","first-page":"e7179","DOI":"10.1002\/cpe.7179","article-title":"Covid-19 detection from radiographs by feature-reinforced ensemble learning","volume":"34","author":"Elen","year":"2022","journal-title":"Concurrency and Computation: Practice and Experience"},{"key":"10.1016\/j.neunet.2026.108715_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2020.106855","article-title":"Standardized variable distances: A distance-based machine learning method","volume":"98","author":"Elen","year":"2021","journal-title":"Applied Soft Computing"},{"issue":"13-15","key":"10.1016\/j.neunet.2026.108715_bib0012","doi-asserted-by":"crossref","first-page":"1728","DOI":"10.1016\/j.neucom.2006.01.004","article-title":"Improved pruning strategy for radial basis function networks with dynamic decay adjustment","volume":"69","author":"Elisa","year":"2006","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neunet.2026.108715_bib0013","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2024.1352935","article-title":"Semantic segmentation of microbial alterations based on SegFormer","volume":"15","author":"Elmessery","year":"2024","journal-title":"Frontiers in Plant Science"},{"key":"10.1016\/j.neunet.2026.108715_bib0014","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2015). Deep residual learning for image recognition. arXiv. 10.48550\/ARXIV.1512.03385.","DOI":"10.1109\/CVPR.2016.90"},{"issue":"2","key":"10.1016\/j.neunet.2026.108715_bib0015","doi-asserted-by":"crossref","first-page":"215","DOI":"10.29220\/CSAM.2023.30.2.215","article-title":"Recent deep learning methods for tabular data","volume":"30","author":"Hwang","year":"2023","journal-title":"Communications for Statistical Applications and Methods"},{"issue":"20","key":"10.1016\/j.neunet.2026.108715_bib0016","doi-asserted-by":"crossref","first-page":"3802","DOI":"10.1016\/j.ins.2008.05.011","article-title":"A modal learning adaptive function neural network applied to handwritten digit recognition","volume":"178","author":"Kang","year":"2008","journal-title":"Information Sciences"},{"issue":"8","key":"10.1016\/j.neunet.2026.108715_bib0017","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/a15080273","article-title":"Communication-efficient vertical federated learning","volume":"15","author":"Khan","year":"2022","journal-title":"Algorithms"},{"key":"10.1016\/j.neunet.2026.108715_bib0018","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"issue":"12","key":"10.1016\/j.neunet.2026.108715_bib0019","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0295598","article-title":"A comparative analysis of converters of tabular data into image for the classification of arboviruses using convolutional neural networks","volume":"18","author":"Medeiros Neto","year":"2023","journal-title":"PLoS ONE"},{"key":"10.1016\/j.neunet.2026.108715_bib0020","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1007\/978-3-319-26532-2_74","article-title":"Prototype selection on large and streaming data","author":"Meena","year":"2015","journal-title":"Lecture Notes in Computer Science"},{"issue":"15","key":"10.1016\/j.neunet.2026.108715_bib0021","doi-asserted-by":"crossref","first-page":"1817","DOI":"10.3390\/math9151817","article-title":"Classification of diseases using machine learning algorithms: A comparative study","volume":"9","author":"Moreno-Ibarra","year":"2021","journal-title":"Mathematics"},{"issue":"1","key":"10.1016\/j.neunet.2026.108715_bib0022","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1186\/s40537-024-00944-3","article-title":"Feature reduction for hepatocellular carcinoma prediction using machine learning algorithms","volume":"11","author":"Mostafa","year":"2024","journal-title":"Journal of Big Data"},{"key":"10.1016\/j.neunet.2026.108715_bib0023","series-title":"Intelligent Distributed Computing XVI","first-page":"85","article-title":"Towards application of the tabular data transformation to images in the intrusion detection tasks using deep learning techniques","author":"Novikova","year":"2024"},{"issue":"7","key":"10.1016\/j.neunet.2026.108715_bib0024","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1049\/el:20057296","article-title":"Integrated method for constructive training of radial basis function networks","volume":"41","author":"Oliveira","year":"2005","journal-title":"Electronics Letters"},{"key":"10.1016\/j.neunet.2026.108715_bib0025","series-title":"Proceedings of the international conference on pattern recognition (ICPR 2004)","first-page":"625","article-title":"Improving RBF-DDA performance on optical character recognition through parameter selection","author":"Oliveira","year":"2004"},{"issue":"21","key":"10.1016\/j.neunet.2026.108715_bib0026","doi-asserted-by":"crossref","first-page":"14975","DOI":"10.1007\/s00521-021-06133-0","article-title":"Improved machine learning performances with transfer learning to predicting need for hospitalization in arboviral infections against the small dataset","volume":"33","author":"Ozer","year":"2021","journal-title":"Neural Computing and Applications"},{"key":"10.1016\/j.neunet.2026.108715_bib0027","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.omega.2015.05.009","article-title":"Constrained subspace classifier for high dimensional datasets","volume":"59","author":"Panagopoulos","year":"2016","journal-title":"Omega"},{"key":"10.1016\/j.neunet.2026.108715_bib0028","series-title":"Emerging technologies in data mining and information security. Advances in intelligent systems and computing","article-title":"Heart diseases prediction system using CHC-TSS evolutionary, KNN, and decision tree classification algorithm","volume":"813","author":"Saxena","year":"2019"},{"key":"10.1016\/j.neunet.2026.108715_bib0029","unstructured":"Sharma, A. (2012). Handwritten digit recognition using support vector machine. arXiv. 10.48550\/arXiv.1203.3847."},{"key":"10.1016\/j.neunet.2026.108715_bib0030","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.inffus.2021.11.011","article-title":"Tabular data: Deep learning is not all you need","volume":"81","author":"Shwartz-Ziv","year":"2022","journal-title":"Information Fusion"},{"key":"10.1016\/j.neunet.2026.108715_bib0031","doi-asserted-by":"crossref","first-page":"9741","DOI":"10.1007\/s13369-021-06377-x","article-title":"Evaluating the performance of data level methods using KEEL tool to address class imbalance problem","volume":"47","author":"Upadhyay","year":"2022","journal-title":"Arabian Journal for Science and Engineering"},{"key":"10.1016\/j.neunet.2026.108715_bib0032","series-title":"Proceedings of the 14th international conference on frontiers in handwriting recognition","first-page":"429","article-title":"A neural network based distance function for the k-nearest neighbor classifier","author":"Vajda","year":"2014"},{"key":"10.1016\/j.neunet.2026.108715_bib0033","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.119535","article-title":"Random feature selection using random subspace logistic regression","volume":"217","author":"Wichitaksorn","year":"2023","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"10.1016\/j.neunet.2026.108715_bib0034","article-title":"Converting tabular data into images for deep learning with convolutional neural networks","volume":"11","author":"Zhu","year":"2021","journal-title":"Scientific Reports"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026001772?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026001772?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T22:43:09Z","timestamp":1776465789000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026001772"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":34,"alternative-id":["S0893608026001772"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.108715","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Transforming tabular data into images for deep learning models","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.108715","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"108715"}}