{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T00:10:41Z","timestamp":1772496641625,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T00:00:00Z","timestamp":1695081600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007446","name":"Deanship of Scientific Research at King Khalid University","doi-asserted-by":"publisher","award":["RGP2\/35\/44"],"award-info":[{"award-number":["RGP2\/35\/44"]}],"id":[{"id":"10.13039\/501100007446","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007446","name":"Deanship of Scientific Research at King Khalid University","doi-asserted-by":"publisher","award":["PNURSP2023R361"],"award-info":[{"award-number":["PNURSP2023R361"]}],"id":[{"id":"10.13039\/501100007446","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007446","name":"Deanship of Scientific Research at King Khalid University","doi-asserted-by":"publisher","award":["RSP2023R459"],"award-info":[{"award-number":["RSP2023R459"]}],"id":[{"id":"10.13039\/501100007446","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004242","name":"Princess Nourah bint Abdulrahman University Researchers Supporting Project","doi-asserted-by":"publisher","award":["RGP2\/35\/44"],"award-info":[{"award-number":["RGP2\/35\/44"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004242","name":"Princess Nourah bint Abdulrahman University Researchers Supporting Project","doi-asserted-by":"publisher","award":["PNURSP2023R361"],"award-info":[{"award-number":["PNURSP2023R361"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004242","name":"Princess Nourah bint Abdulrahman University Researchers Supporting Project","doi-asserted-by":"publisher","award":["RSP2023R459"],"award-info":[{"award-number":["RSP2023R459"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002383","name":"King Saud University, Riyadh, Saudi Arabia","doi-asserted-by":"publisher","award":["RGP2\/35\/44"],"award-info":[{"award-number":["RGP2\/35\/44"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002383","name":"King Saud University, Riyadh, Saudi Arabia","doi-asserted-by":"publisher","award":["PNURSP2023R361"],"award-info":[{"award-number":["PNURSP2023R361"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002383","name":"King Saud University, Riyadh, Saudi Arabia","doi-asserted-by":"publisher","award":["RSP2023R459"],"award-info":[{"award-number":["RSP2023R459"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Future University in Egypt (FUE)","award":["RGP2\/35\/44"],"award-info":[{"award-number":["RGP2\/35\/44"]}]},{"name":"Future University in Egypt (FUE)","award":["PNURSP2023R361"],"award-info":[{"award-number":["PNURSP2023R361"]}]},{"name":"Future University in Egypt (FUE)","award":["RSP2023R459"],"award-info":[{"award-number":["RSP2023R459"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing imagery involves capturing and examining details about the Earth\u2019s surface from a distance, often using satellites, drones, or other aerial platforms. It offers useful data with which to monitor and understand different phenomena on Earth. Vehicle detection and classification play a crucial role in various applications, including traffic monitoring, urban planning, and environmental analysis. Deep learning, specifically convolutional neural networks (CNNs), has revolutionized vehicle detection in remote sensing. This study designs an improved Chimp optimization algorithm with a DL-based vehicle detection and classification (ICOA-DLVDC) technique on RSI. The presented ICOA-DLVDC technique involves two phases: object detection and classification. For vehicle detection, the ICOA-DLVDC technique applies the EfficientDet model. Next, the detected objects can be classified by using the sparse autoencoder (SAE) model. To optimize the SAE\u2019s hyperparameters effectively, we introduce an ICOA which streamlines the parameter tuning process, accelerating convergence and enhancing the overall performance of the SAE classifier. An extensive set of experiments has been conducted to highlight the improved vehicle classification outcomes of the ICOA-DLVDC technique. The simulation values demonstrated the remarkable performance of the ICOA-DLVDC approach compared to other recent techniques, with a maximum accuracy of 99.70% and 99.50% on the VEDAI dataset and ISPRS Postdam dataset, respectively.<\/jats:p>","DOI":"10.3390\/rs15184600","type":"journal-article","created":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T02:47:52Z","timestamp":1695091672000},"page":"4600","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Exploiting Remote Sensing Imagery for Vehicle Detection and Classification Using an Artificial Intelligence Technique"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1887-6719","authenticated-orcid":false,"given":"Masoud","family":"Alajmi","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia"}]},{"given":"Hayam","family":"Alamro","sequence":"additional","affiliation":[{"name":"Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia"}]},{"given":"Fuad","family":"Al-Mutiri","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Faculty of Sciences and Arts, King Khalid University, Abha 63311, Saudi Arabia"}]},{"given":"Mohammed","family":"Aljebreen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Community College, King Saud University, P.O. Box 28095, Riyadh 11437, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0217-0751","authenticated-orcid":false,"given":"Kamal M.","family":"Othman","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}]},{"given":"Ahmed","family":"Sayed","sequence":"additional","affiliation":[{"name":"Research Center, Future University in Egypt, New Cairo 11835, Egypt"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,19]]},"reference":[{"key":"ref_1","first-page":"168","article-title":"Information Extraction of the Vehicle from High-Resolution Remote Sensing Image Based on Convolution Neural Network","volume":"16","author":"Wang","year":"2023","journal-title":"Recent Adv. Electr. Electron. Eng. (Former. Recent Pat. Electr. Electron. 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