{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T08:09:00Z","timestamp":1775808540183,"version":"3.50.1"},"reference-count":32,"publisher":"Tech Science Press","issue":"1","license":[{"start":{"date-parts":[[2025,3,30]],"date-time":"2025-03-30T00:00:00Z","timestamp":1743292800000},"content-version":"vor","delay-in-days":88,"URL":"https:\/\/doi.org\/10.32604\/TSP-CROSSMARKPOLICY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.059301","type":"journal-article","created":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T01:46:58Z","timestamp":1742953618000},"page":"1367-1398","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":14,"title":["xCViT: Improved Vision Transformer Network with Fusion of CNN and Xception for Skin Disease Recognition with Explainable AI"],"prefix":"10.32604","volume":"83","author":[{"given":"Armughan","family":"Ali","sequence":"first","affiliation":[]},{"given":"Hooria","family":"Shahbaz","sequence":"additional","affiliation":[]},{"given":"Robertas","family":"Dama\u0161evi\u010dius","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"741","DOI":"10.1016\/j.jaad.2005.08.063","article-title":"Skin cancer in skin of color","volume":"55","author":"Gloster","year":"2006","journal-title":"J Am Acad Dermatol"},{"key":"ref2","first-page":"110","article-title":"Non-melanoma skin cancer: statistical associations between clinical parameters","volume":"48","author":"Ciuciulete","year":"2022","journal-title":"Curr Health Sci J"},{"key":"ref3","first-page":"831","article-title":"Intelligent multiclass skin cancer detection using convolution neural networks","volume":"69","author":"Alabduljabbar","year":"2021","journal-title":"Comput Mater Contin"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"104968","DOI":"10.1016\/j.bspc.2023.104968","article-title":"Skin cancer detection using dual optimization based deep learning network","volume":"84","author":"Gomathi","year":"2023","journal-title":"Biomed Signal Process Contr"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"e22971","DOI":"10.1002\/ima.22971","article-title":"Skin cancer classification using improved transfer learning model-based random forest classifier and golden search optimization","volume":"34","author":"Vidhyalakshmi","year":"2024","journal-title":"Int J Imaging Syst Tech"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"2793","DOI":"10.1016\/j.procs.2024.04.264","article-title":"Skin cancer detection and classification using deep learning techniques","volume":"235","author":"Kavitha","year":"2024","journal-title":"Procedia Comput Sci"},{"key":"ref7","unstructured":"Islam N, Hasib KM, Joti FA, Karim A, Azam S. Leveraging knowledge distillation for lightweight skin cancer classification: balancing accuracy and computational efficiency. arXiv:2406.17051. 2024."},{"key":"ref8","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.3390\/diagnostics14131359","article-title":"An intelligent mechanism to detect multi-factor skin cancer","volume":"14","author":"Abdullah","year":"2024","journal-title":"Diagnostics"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"557","DOI":"10.3390\/a17120557","article-title":"Integrating explanations into CNNs by adopting spiking attention block for skin cancer detection","volume":"17","author":"Nasir","year":"2024","journal-title":"Algorithms"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"1324042","DOI":"10.3389\/fphys.2023.1324042","article-title":"Melanoma skin cancer detection using mask-RCNN with modified GRU model","volume":"14","author":"Monica","year":"2024","journal-title":"Front Physiol"},{"key":"ref11","first-page":"S39","article-title":"CACBL-Net: a lightweight skin cancer detection system for portable diagnostic devices using deep learning based channel attention and adaptive class balanced focal loss function","volume":"35","author":"Agrawal","year":"2024","journal-title":"Multimed Tools Appl"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1186\/s43042-024-00522-5","article-title":"Artificial intelligence-driven enhanced skin cancer diagnosis: leveraging convolutional neural networks with discrete wavelet transformation","volume":"25","author":"Angelin Claret","year":"2024","journal-title":"Egypt J Med Hum Genet"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"1342","DOI":"10.3390\/electronics12061342","article-title":"A deep-ensemble-learning-based approach for skin cancer diagnosis","volume":"12","author":"Shehzad","year":"2023","journal-title":"Electronics"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"2869","DOI":"10.3390\/diagnostics13182869","article-title":"SkinNet-INIO: multiclass skin lesion localization and classification using fusion-assisted deep neural networks and improved nature-inspired optimization algorithm","volume":"13","author":"Hussain","year":"2023","journal-title":"Diagnostics"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.neunet.2023.01.022","volume":"160","author":"Maqsood","year":"2023","journal-title":"Neural Netw"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"124584","DOI":"10.1016\/j.eswa.2024.124584","article-title":"MOX-NET: multi-stage deep hybrid feature fusion and selection framework for monkeypox classification","volume":"255","author":"Maqsood","year":"2024","journal-title":"Expert Syst Appl"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"2137","DOI":"10.1002\/ima.22750","article-title":"Melanoma segmentation: a framework of improved DenseNet77 and UNET convolutional neural network","volume":"32","author":"Nawaz","year":"2022","journal-title":"Int J Imaging Syst Tech"},{"key":"ref18","first-page":"819","article-title":"Melanoma diagnosis using enhanced faster region convolutional neural networks optimized by artificial gorilla troops algorithm","volume":"52","author":"Nivedha","year":"2023","journal-title":"Inf Technol Contr"},{"key":"ref19","first-page":"288","article-title":"Monkeypox disease detection with pretrained deep learning models","volume":"52","author":"Ren","year":"2023","journal-title":"Inf Technol Contr"},{"key":"ref20","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, et al. An image is worth 16 \u00d7 16 words: transformers for image recognition at scale. arXiv:2010.11929. 2020."},{"key":"ref21","series-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"1800","article-title":"Xception: deep learning with depthwise separable convolutions","author":"Chollet","year":"2017 Jul 21\u201326"},{"key":"ref22","unstructured":"Howard AG, Zhu M, Chen B, Kalenichenko D, Wang W, Weyand T, et al. MobileNets: efficient convolutional neural networks for mobile vision applications. arXiv:1704.04861. 2017."},{"key":"ref23","series-title":"2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"618","author":"Selvaraju","year":"2017 Oct 22\u201329"},{"key":"ref24","series-title":"Proceedings of 1st International Conference on Image Processing","first-page":"168","article-title":"Two deterministic half-quadratic regularization algorithms for computed imaging","author":"Charbonnier","year":"1994 Nov 13\u201316"},{"key":"ref25","unstructured":"Loshchilov I, Hutter F. Decoupled weight decay regularization. arXiv:1711.05101. 2017."},{"key":"ref26","unstructured":"Loshchilov I, Hutter F. SGDR: stochastic gradient descent with warm restarts. arXiv:1608.03983. 2016."},{"key":"ref27","first-page":"47","article-title":"Mobile-based skin disease diagnosis system using convolutional neural networks (CNN)","volume":"14","author":"Maduranga","year":"2022","journal-title":"Int J Image Graph Signal Process"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"112193","DOI":"10.1109\/ACCESS.2021.3103410","article-title":"Skin lesion classification by ensembles of deep convolutional networks and regularly spaced shifting","volume":"9","author":"Thurnhofer-Hemsi","year":"2021","journal-title":"IEEE Access"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"2852","DOI":"10.3390\/s21082852","article-title":"Classification of skin disease using deep learning neural networks with MobileNet V2 and LSTM","volume":"21","author":"Srinivasu","year":"2021","journal-title":"Sensors"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"2677","DOI":"10.3390\/app12052677","article-title":"Multiclass skin lesion classification using a novel lightweight deep learning framework for smart healthcare","volume":"12","author":"Hoang","year":"2022","journal-title":"Appl Sci"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"105351","DOI":"10.1016\/j.cmpb.2020.105351","volume":"190","author":"Al-Masni","year":"2020","journal-title":"Comput Methods Programs Biomed"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"21","DOI":"10.38094\/jastt301121","article-title":"Skin lesion classification based on convolutional neural network","volume":"3","author":"Agyenta","year":"2022","journal-title":"J Appl Sci Technol Trends"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-83-1\/TSP_CMC_59301\/TSP_CMC_59301.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T06:34:18Z","timestamp":1763102058000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v83n1\/60070"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.059301","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2024-10-03","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-19","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-03-26","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}