{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T10:12:06Z","timestamp":1776939126313,"version":"3.51.4"},"reference-count":31,"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.2025.061890","type":"journal-article","created":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T04:19:16Z","timestamp":1742185156000},"page":"1023-1039","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":7,"title":["Mango Disease Detection Using Fused Vision Transformer with ConvNeXt Architecture"],"prefix":"10.32604","volume":"83","author":[{"given":"Faten S.","family":"Alamri","sequence":"first","affiliation":[]},{"given":"Tariq","family":"Sadad","sequence":"additional","affiliation":[]},{"given":"Ahmed S.","family":"Almasoud","sequence":"additional","affiliation":[]},{"given":"Raja Atif","family":"Aurangzeb","sequence":"additional","affiliation":[]},{"given":"Amjad","family":"Khan","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"102216","DOI":"10.1016\/j.ecoinf.2023.102216","article-title":"Enhancing mango disease diagnosis through eco-informatics: a deep learning approach","volume":"77","author":"Ali Salamai","year":"2023","journal-title":"Ecol Inform"},{"key":"ref2","series-title":"2021 International Conference on Intelligent Technologies (CONIT)","article-title":"Identification of artificially ripen mango using aroma and texture features","author":"Shah","year":"2021 Jun 25\u201327"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"173","DOI":"10.3390\/foods12010173","article-title":"Research progress on mango post-harvest ripening physiology and the regulatory technologies","volume":"12","author":"Liu","year":"2023","journal-title":"Foods"},{"key":"ref4","series-title":"2024 International Conference on Emerging Innovations and Advanced Computing (INNOCOMP)","article-title":"Comparative evaluation of mango fruit diseases classification using machine learning","author":"Kumar","year":"2024 May 25\u201326"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"1168203","DOI":"10.3389\/fmicb.2023.1168203","article-title":"Mango anthracnose disease: the current situation and direction for future research","volume":"14","author":"Dofuor","year":"2023","journal-title":"Front Microbiol"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"108260","DOI":"10.1016\/j.engappai.2024.108260","article-title":"Fruit and vegetable disease detection and classification: recent trends, challenges, and future opportunities","volume":"133","author":"Gupta","year":"2024","journal-title":"Eng Appl Artif Intell"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"109466","DOI":"10.1016\/j.engappai.2024.109466","article-title":"Plant leaf disease identification by parameter-efficient transformer with adapter","volume":"138","author":"Xu","year":"2024","journal-title":"Eng Appl Artif Intell"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"3717","DOI":"10.22214\/ijraset.2019.4624","article-title":"Mango disease detection using image processing","volume":"7","author":"Veling","year":"2019","journal-title":"Int J Res Appl Sci Eng Technol"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"105842","DOI":"10.1016\/j.compag.2020.105842","article-title":"Data augmentation for automated pest classification in Mango farms","volume":"179","author":"Kusrini","year":"2020","journal-title":"Comput Electron Agric"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"16","DOI":"10.4236\/jcc.2022.1012002","article-title":"Mango diseases classification solutions using machine learning or deep learning: a review","volume":"10","author":"Faye","year":"2022","journal-title":"J Comput Commun"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s42044-020-00057-z","article-title":"Mango leaf diseases recognition using neural network and support vector machine","volume":"3","author":"Mia","year":"2020","journal-title":"Iran J Comput Sci"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"75718","DOI":"10.1109\/ACCESS.2024.3404651","article-title":"Internet of Things (IoT)-enabled machine learning models for efficient monitoring of smart agriculture","volume":"12","author":"Aldossary","year":"2024","journal-title":"IEEE Access"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"108941","DOI":"10.1016\/j.dib.2023.108941","article-title":"MangoLeafBD: a comprehensive image dataset to classify diseased and healthy mango leaves","volume":"47","author":"Ahmed","year":"2023","journal-title":"Data Brief"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"9211700","DOI":"10.1155\/2022\/9211700","article-title":"Design and evaluation of a hybrid technique for detecting sunflower leaf disease using deep learning approach","volume":"2022","author":"Malik","year":"2022","journal-title":"J Food Qual"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/15538362.2021.2023069","article-title":"Classification and grading of harvested mangoes using convolutional neural network","volume":"22","author":"Rizwan Iqbal","year":"2022","journal-title":"Int J Fruit Sci"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"11901","DOI":"10.3390\/app112411901","article-title":"Mango leaf disease recognition and classification using novel segmentation and vein pattern technique","volume":"11","author":"Saleem","year":"2021","journal-title":"Appl Sci"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"109636","DOI":"10.1016\/j.compag.2024.109636","article-title":"Enhanced detection of mango leaf diseases in field environments using MSMP-CNN and transfer learning","volume":"227","author":"Chen","year":"2024","journal-title":"Comput Electron Agric"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"6387","DOI":"10.1109\/JSEN.2016.2580221","article-title":"A machine vision technique for grading of harvested mangoes based on maturity and quality","volume":"16","author":"Nandi","year":"2016","journal-title":"IEEE Sens J"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1007\/s40030-019-00396-6","article-title":"Common external defect detection of mangoes using color computer vision","volume":"100","author":"Patel","year":"2019","journal-title":"J Inst Eng Ind Ser A"},{"key":"ref20","first-page":"5","article-title":"Defect identification and maturity detection of mango fruits using image analysis","volume":"1","author":"Sahu","year":"2017","journal-title":"Am J Artif Intell"},{"key":"ref21","first-page":"3755","article-title":"Automated detection and classification of mango fruit diseases using a novel WOA-QRNN technique on infected mango fruit images through transfer learning","volume":"12","author":"Kalaivani","year":"2023","journal-title":"Int J Intell Syst Appl Eng"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"13711","DOI":"10.1109\/ACCESS.2024.3356551","article-title":"A study of ConvNeXt architectures for enhanced image captioning","volume":"12","author":"Ramos","year":"2024","journal-title":"IEEE Access"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"2385","DOI":"10.3390\/s23052385","article-title":"Vision transformers in image restoration: a survey","volume":"23","author":"Ali","year":"2023","journal-title":"Sensors"},{"key":"ref24","unstructured":"Faye D, Diop I, Mbaye N, Diedhiou MM, Dione D. SenMangoFruitDDS. [cited 2025 Jan 1]. Available from: https:\/\/SenMangoFruitDDS-MendeleyData."},{"key":"ref25","unstructured":"Rahman MM, Kowser KA, Islam M, Arefin MN, Shah A, et al. Mango leaf disease identification dataset: (MLDID); [cited 2025 Jan 1] Available from: https:\/\/MangoLeafDiseaseIdentificationDataset:(MLDID)-MendeleyData."},{"key":"ref26","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s13640-021-00558-2","article-title":"A probabilistic segmentation and entropy-rank correlation-based feature selection approach for the recognition of fruit diseases","volume":"2021","author":"Khan","year":"2021","journal-title":"EURASIP J Image Video Process"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.compag.2018.10.013","article-title":"CCDF: automatic system for segmentation and recognition of fruit crops diseases based on correlation coefficient and deep CNN features","volume":"155","author":"Khan","year":"2018","journal-title":"Comput Electron Agric"},{"key":"ref28","series-title":"2023 International Conference on Electrical, Computer and Communication Engineering","article-title":"Detect Bangladeshi mango leaf diseases using lightweight convolutional neural network","author":"Mahbub","year":"2023 Feb 23\u201325"},{"key":"ref29","first-page":"100787","article-title":"LeafNet: a proficient convolutional neural network for detecting seven prominent mango leaf diseases","volume":"14","author":"Rizvee","year":"2023","journal-title":"J Agric Food Res"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"28","DOI":"10.28991\/ESJ-2024-08-01-03","article-title":"Light-weight deep learning model for accelerating the classification of mango-leaf disease","volume":"8","author":"Mahmud","year":"2024","journal-title":"Emerg Sci J"},{"key":"ref31","series-title":"The International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability","article-title":"MangoFruitDDS: a standard mango fruit diseases dataset made in Africa","author":"Faye","year":"2023 Oct 18\u201320"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-83-1\/TSP_CMC_61890\/TSP_CMC_61890.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T06:40:44Z","timestamp":1763102444000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v83n1\/60127"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":31,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.061890","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2024-12-05","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-11","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"}}]}}