{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T19:26:36Z","timestamp":1783106796247,"version":"3.54.6"},"reference-count":63,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372325"],"award-info":[{"award-number":["62372325"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62561004"],"award-info":[{"award-number":["62561004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011785","name":"Guangxi Science and Technology Department","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011785","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018571","name":"Specific Research Project of Guangxi for Research Bases and Talents","doi-asserted-by":"publisher","award":["AD25069071"],"award-info":[{"award-number":["AD25069071"]}],"id":[{"id":"10.13039\/501100018571","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006606","name":"Tianjin Municipal Natural Science Foundation","doi-asserted-by":"publisher","award":["23JCZDJC00280"],"award-info":[{"award-number":["23JCZDJC00280"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.eswa.2026.132573","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T17:52:20Z","timestamp":1777571540000},"page":"132573","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Domain adaptive object detection via CLIP-space guidance and LoRA fine-tuning"],"prefix":"10.1016","volume":"326","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9281-5993","authenticated-orcid":false,"given":"Enze","family":"Qi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6587-0360","authenticated-orcid":false,"given":"Kan","family":"Chang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7377-8911","authenticated-orcid":false,"given":"Mingyang","family":"Ling","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0169-1273","authenticated-orcid":false,"given":"Qingzhi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-6277-1381","authenticated-orcid":false,"given":"Xueyu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1196-6615","authenticated-orcid":false,"given":"Yehua","family":"Ling","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3933-774X","authenticated-orcid":false,"given":"Yujian","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2182-5741","authenticated-orcid":false,"given":"Zan","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.132573_bib0001","series-title":"Proceedings of the annual meeting of the association for computational linguistics and the international joint conference on natural language processing(ACL\/IJCNLP)","first-page":"7319","article-title":"Intrinsic dimensionality explains the effectiveness of language model fine-tuning","author":"Aghajanyan","year":"2021"},{"key":"10.1016\/j.eswa.2026.132573_bib0002","series-title":"IEEE\/CVF Winter conference on applications of computer vision (WACV)","first-page":"1266","article-title":"Multi-source domain adaptation for object detection with prototype-based mean teacher","author":"Belal","year":"2024"},{"key":"10.1016\/j.eswa.2026.132573_bib0003","series-title":"Neural networks: Tricks of the trade - second edition","first-page":"421","article-title":"Stochastic gradient descent tricks","volume":"vol. 7700","author":"Bottou","year":"2012"},{"key":"10.1016\/j.eswa.2026.132573_bib0004","series-title":"Advances in neural information processing systems (NeurIPS)","first-page":"1877","article-title":"Language models are few-shot learners","author":"Brown","year":"2020"},{"key":"10.1016\/j.eswa.2026.132573_bib0005","series-title":"IEEE Conference on computer vision and pattern recognition (CVPR)","first-page":"11457","article-title":"Exploring object relation in mean teacher for cross-domain detection","author":"Cai","year":"2019"},{"key":"10.1016\/j.eswa.2026.132573_bib0006","series-title":"IEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"23839","article-title":"Contrastive mean teacher for domain adaptive object detectors","author":"Cao","year":"2023"},{"key":"10.1016\/j.eswa.2026.132573_bib0007","series-title":"European conference on computer vision (ECCV)","first-page":"55","article-title":"Adaclip: Adapting CLIP with hybrid learnable prompts for zero-shot anomaly detection","volume":"vol. 15093","author":"Cao","year":"2024"},{"key":"10.1016\/j.eswa.2026.132573_bib0008","series-title":"International conference on machine learning (ICML)","first-page":"3040","article-title":"Learning domain adaptive object detection with probabilistic teacher","volume":"vol. 162","author":"Chen","year":"2022"},{"key":"10.1016\/j.eswa.2026.132573_bib0009","series-title":"2018\u202fIEEE Conference on computer vision and pattern recognition (CVPR)","first-page":"3339","article-title":"Domain adaptive faster R-CNN for object detection in the wild","author":"Chen","year":"2018"},{"key":"10.1016\/j.eswa.2026.132573_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129435","article-title":"Focusing on feature-level domain alignment with text semantic for weakly-supervised domain adaptive object detection","volume":"622","author":"Chen","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.132573_bib0011","unstructured":"Das, S., Romanelli, M., Tran, C., Reza, Z., Kailkhura, B., & Fioretto, F. (2024). Low-rank finetuning for LLMs: A fairness perspective. arXiv preprint arXiv: 2405.18572."},{"key":"10.1016\/j.eswa.2026.132573_bib0012","series-title":"Asian conference on computer vision (ACCV)","first-page":"312","article-title":"Auxiliary domain-guided adaptive object detection in adverse weather conditions","volume":"vol. 15472","author":"Fu","year":"2024"},{"issue":"4","key":"10.1016\/j.eswa.2026.132573_bib0013","doi-asserted-by":"crossref","first-page":"141:1","DOI":"10.1145\/3528223.3530164","article-title":"StyleGAN-NADA: CLIP-guided domain adaptation of image generators","volume":"41","author":"Gal","year":"2022","journal-title":"ACM Transactions on Graphics"},{"key":"10.1016\/j.eswa.2026.132573_bib0014","series-title":"2015\u202fIEEE International conference on computer vision (ICCV)","first-page":"1440","article-title":"Fast R-CNN","author":"Girshick","year":"2015"},{"key":"10.1016\/j.eswa.2026.132573_bib0015","series-title":"2nd international conference on learning representations (ICLR)","article-title":"An empirical investigation of catastrophic forgeting in gradient-based neural networks","author":"Goodfellow","year":"2014"},{"key":"10.1016\/j.eswa.2026.132573_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127101","article-title":"Enhancing domain adaptation for plant diseases detection through masked image consistency in multi-granularity alignment","volume":"276","author":"Guo","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.132573_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106906","article-title":"Reconsidering learnable fine-grained text prompts for few-shot anomaly detection in visual-language models","volume":"182","author":"Han","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.eswa.2026.132573_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106733","article-title":"Illumination-aware divide-and-conquer network for improperly-exposed image enhancement","volume":"180","author":"Han","year":"2024","journal-title":"Neural Networks"},{"key":"10.1016\/j.eswa.2026.132573_bib0019","first-page":"1","article-title":"Remote sensing teacher: Cross-domain detection transformer with learnable frequency-enhanced feature alignment in remote sensing imagery","volume":"62","author":"Han","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132573_bib0020","series-title":"The tenth international conference on learning representations (ICLR)","article-title":"Towards a unified view of parameter-efficient transfer learning","author":"He","year":"2022"},{"key":"10.1016\/j.eswa.2026.132573_bib0021","series-title":"The association for the advancement of artificial intelligence (AAAI)","first-page":"17150","article-title":"Differential alignment for domain adaptive object detection","author":"He","year":"2025"},{"key":"10.1016\/j.eswa.2026.132573_bib0022","series-title":"2019 IEEE\/CVF International conference on computer vision (ICCV)","first-page":"6667","article-title":"Multi-adversarial faster-RCNN for unrestricted object detection","author":"He","year":"2019"},{"key":"10.1016\/j.eswa.2026.132573_bib0023","series-title":"2021\u202fIEEE International conference on image processing (ICIP))","first-page":"3323","article-title":"Multiscale domain adaptive yolo for cross-domain object detection","author":"Hnewa","year":"2021"},{"key":"10.1016\/j.eswa.2026.132573_bib0024","doi-asserted-by":"crossref","first-page":"1857","DOI":"10.1109\/TIP.2023.3255106","article-title":"Integrated multiscale domain adaptive YOLO","volume":"32","author":"Hnewa","year":"2023","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.132573_bib0025","series-title":"Proceedings of the 36th international conference on machine learning (ICML)","first-page":"2790","article-title":"Parameter-efficient transfer learning for NLP","volume":"vol. 97","author":"Houlsby","year":"2019"},{"key":"10.1016\/j.eswa.2026.132573_bib0026","series-title":"The tenth international conference on learning representations (ICLR)","article-title":"LoRA: Low-rank adaptation of large language models","author":"Hu","year":"2022"},{"key":"10.1016\/j.eswa.2026.132573_bib0027","article-title":"Unsupervised domain adaptation with hierarchical masked dual-adversarial network for end-to-end classification of multisource remote sensing data","volume":"63","author":"Hu","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132573_bib0028","series-title":"IEEE\/CVF International conference on computer vision (ICCV)","first-page":"752","article-title":"Semask: Semantically masked transformers for semantic segmentation","author":"Jain","year":"2023"},{"key":"10.1016\/j.eswa.2026.132573_bib0029","unstructured":"Jocher, G. (2020). Yolov5. https:\/\/github.com\/ultralytics\/yolov5."},{"key":"10.1016\/j.eswa.2026.132573_bib0030","doi-asserted-by":"crossref","first-page":"11316","DOI":"10.1109\/TMM.2024.3453061","article-title":"VLDadaptor: Domain adaptive object detection with vision-language model distillation","volume":"26","author":"Ke","year":"2024","journal-title":"IEEE Transactions on Multimedia"},{"key":"10.1016\/j.eswa.2026.132573_bib0031","unstructured":"Kenk, M. A., & Hassaballah, M. (2020). DAWN: Vehicle detection in adverse weather nature dataset. arXiv preprint arXiv: 2008.05402."},{"key":"10.1016\/j.eswa.2026.132573_bib0032","series-title":"IEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"16541","article-title":"CAT: Exploiting inter-class dynamics for domain adaptive object detection","author":"Kennerley","year":"2024"},{"key":"10.1016\/j.eswa.2026.132573_bib0033","series-title":"Proceedings of the 2021 conference on empirical methods in natural language processing (EMNLP)","first-page":"3045","article-title":"The power of scale for parameter-efficient prompt tuning","author":"Lester","year":"2021"},{"key":"10.1016\/j.eswa.2026.132573_bib0034","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1109\/TIP.2018.2867951","article-title":"Benchmarking single-image dehazing and beyond","volume":"28","author":"Li","year":"2019","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.132573_bib0035","series-title":"International conference on learning representations(ICLR)","article-title":"Measuring the intrinsic dimension of objective landscapes","author":"Li","year":"2018"},{"issue":"3","key":"10.1016\/j.eswa.2026.132573_bib0036","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1109\/TIV.2022.3165353","article-title":"Cross-domain object detection for autonomous driving: A stepwise domain adaptative YOLO approach","volume":"7","author":"Li","year":"2022","journal-title":"IEEE Transactions on Intelligent Vehicles"},{"key":"10.1016\/j.eswa.2026.132573_bib0037","series-title":"Advances in neural information processing systems (NeurIPS)","first-page":"4248","article-title":"Learning domain-aware detection head with prompt tuning","author":"Li","year":"2023"},{"key":"10.1016\/j.eswa.2026.132573_bib0038","series-title":"Advances in neural information processing systems (NeurIPS)","first-page":"103574","article-title":"Da-ada: Learning domain-aware adapter for domain adaptive object detection","author":"Li","year":"2024"},{"issue":"5","key":"10.1016\/j.eswa.2026.132573_bib0039","doi-asserted-by":"crossref","first-page":"5405","DOI":"10.1109\/TPAMI.2026.3651700","article-title":"Clip-powered domain generalisation and domain adaptation: A comprehensive survey","volume":"48","author":"Li","year":"2026","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"2","key":"10.1016\/j.eswa.2026.132573_bib0040","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1109\/TIV.2024.3419689","article-title":"Domain adaptation based object detection for autonomous driving in foggy and rainy weather","volume":"10","author":"Li","year":"2025","journal-title":"IEEE Transactions on Intelligent Vehicles"},{"key":"10.1016\/j.eswa.2026.132573_bib0041","series-title":"Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing (ACL\/IJCNLP)","first-page":"4582","article-title":"Prefix-tuning: Optimising continuous prompts for generation","author":"Li","year":"2021"},{"key":"10.1016\/j.eswa.2026.132573_bib0042","series-title":"IEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"7571","article-title":"Cross-domain adaptive teacher for object detection","author":"Li","year":"2022"},{"key":"10.1016\/j.eswa.2026.132573_bib0043","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126400","article-title":"Prompt-induced prototype alignment for few-shot unsupervised domain adaptation","volume":"269","author":"Li","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.132573_bib0044","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1109\/TCI.2024.3374084","article-title":"PRNet: Pyramid restoration network for RAW image super-resolution","volume":"10","author":"Ling","year":"2024","journal-title":"IEEE Transactions Computational Imaging"},{"key":"10.1016\/j.eswa.2026.132573_bib0045","series-title":"Advances in neural information processing systems (NeurIPS)","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"Paszke","year":"2019"},{"key":"10.1016\/j.eswa.2026.132573_bib0046","series-title":"2021 IEEE\/CVF International conference on computer vision (ICCV)","first-page":"2065","article-title":"StyleCLIP: Text-driven manipulation of styleGAN imagery","author":"Patashnik","year":"2021"},{"key":"10.1016\/j.eswa.2026.132573_bib0047","series-title":"Proceedings of the 38th international conference on machine learning (ICML)","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume":"vol. 139","author":"Radford","year":"2021"},{"key":"10.1016\/j.eswa.2026.132573_bib0048","series-title":"2016\u202fIEEE Conference on computer vision and pattern recognition (CVPR)","first-page":"779","article-title":"You only look once: Unified, real-time object detection","author":"Redmon","year":"2016"},{"issue":"6","key":"10.1016\/j.eswa.2026.132573_bib0049","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.132573_bib0050","series-title":"IEEE Conference on computer vision and pattern recognition (CVPR)","first-page":"6956","article-title":"Strong-weak distribution alignment for adaptive object detection","author":"Saito","year":"2019"},{"key":"10.1016\/j.eswa.2026.132573_bib0051","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129448","article-title":"GlobalCLIP: Zero-shot manufacturing anomaly detection with adaptive self-cyclic emsemble learning","volume":"298","author":"Shen","year":"2026","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.132573_bib0052","series-title":"IEEE\/CVF International conference on computer vision (ICCV)","first-page":"4357","article-title":"AD-CLIP: Adapting domains in prompt space using CLIP","author":"Singha","year":"2023"},{"key":"10.1016\/j.eswa.2026.132573_bib0053","series-title":"Advances in neural information processing systems (NeurIPS)","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"Tarvainen","year":"2017"},{"key":"10.1016\/j.eswa.2026.132573_bib0054","first-page":"1","article-title":"Yolov12: Attention-centric real-time object detectors","volume":"abs\/2502.12524","author":"Tian","year":"2025","journal-title":"CoRR"},{"key":"10.1016\/j.eswa.2026.132573_bib0055","series-title":"IEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"837","article-title":"Single-domain generalised object detection in urban scene via cyclic-disentangled self-distillation","author":"Wu","year":"2022"},{"key":"10.1016\/j.eswa.2026.132573_bib0056","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2026.115365","article-title":"UECNet: A unified framework for exposure correction utilising region-level prompts","volume":"337","author":"Xia","year":"2026","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.eswa.2026.132573_bib0057","series-title":"2025IEEE International conference on multimedia and expo (ICME)","first-page":"1","article-title":"Prompt-based two-stage enhancement for low-light object detection","author":"Xiong","year":"2025"},{"key":"10.1016\/j.eswa.2026.132573_bib0058","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111024","article-title":"Versatile teacher: A class-aware teacher-student framework for cross-domain adaptation","volume":"158","author":"Yang","year":"2025","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2026.132573_bib0059","series-title":"2020 IEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"2633","article-title":"BDD100K: a diverse driving dataset for heterogeneous multitask learning","author":"Yu","year":"2020"},{"issue":"12","key":"10.1016\/j.eswa.2026.132573_bib0060","doi-asserted-by":"crossref","first-page":"9161","DOI":"10.1109\/TPAMI.2024.3416098","article-title":"Robust domain adaptive object detection with unified multi-granularity alignment","volume":"46","author":"Zhang","year":"2024","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.132573_bib0061","series-title":"Asian conference on machine learning (ACML)","first-page":"785","article-title":"Domain adaptive YOLO for one-stage cross-domain detection","volume":"vol. 157","author":"Zhang","year":"2021"},{"key":"10.1016\/j.eswa.2026.132573_bib0062","series-title":"IEEE\/CVF Conference on computer vision and pattern recognition (CVPR)","first-page":"16772","article-title":"RegionCLIP: Region-based language-image pretraining","author":"Zhong","year":"2022"},{"issue":"9","key":"10.1016\/j.eswa.2026.132573_bib0063","doi-asserted-by":"crossref","first-page":"2337","DOI":"10.1007\/s11263-022-01653-1","article-title":"Learning to prompt for vision-language models","volume":"130","author":"Zhou","year":"2022","journal-title":"International Journal of Computer Vision"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426014867?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426014867?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T19:07:35Z","timestamp":1783105655000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426014867"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":63,"alternative-id":["S0957417426014867"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132573","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Domain adaptive object detection via CLIP-space guidance and LoRA fine-tuning","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132573","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":"132573"}}