{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T15:36:38Z","timestamp":1778168198690,"version":"3.51.4"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3351003","type":"journal-article","created":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T19:57:22Z","timestamp":1704743842000},"page":"6036-6050","source":"Crossref","is-referenced-by-count":48,"title":["Pest Identification Based on Fusion of Self-Attention With ResNet"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3714-9453","authenticated-orcid":false,"given":"Sk Mahmudul","family":"Hassan","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, VIT-AP University, Amravati, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3320-9965","authenticated-orcid":false,"given":"Arnab Kumar","family":"Maji","sequence":"additional","affiliation":[{"name":"Department of Information Technology, School of Technology, NEHU, Shillong, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1186\/s13007-021-00722-9"},{"issue":"3","key":"ref2","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.biosystemseng.2009.07.002","article-title":"Local feature-based identification and classification\n                        for orchard insects","volume":"104","author":"Wen","year":"2009","journal-title":"Biosyst. Eng."},{"key":"ref3","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.knosys.2012.03.014","article-title":"A new automatic identification system of insect\n                        images at the order level","volume":"33","author":"Wang","year":"2012","journal-title":"Knowl.-Based\n                        Syst."},{"issue":"3","key":"ref4","doi-asserted-by":"crossref","first-page":"190","DOI":"10.25165\/j.ijabe.20181103.3477","article-title":"Classification and recognition scheme for vegetable\n                        pests based on the BOF-SVM model","volume":"11","author":"Xiao","year":"2018","journal-title":"Int. J.\n                        Agricult. Biol. Eng."},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-011-0310-3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.12928\/telkomnika.v15i3.5382"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/srep20410"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/s18124169"},{"key":"ref9","article-title":"Crop pest recognition in natural scenes using\n                        convolutional neural networks","volume":"169","author":"Li","year":"2020","journal-title":"Comput.\n                        Electron. Agricult."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2020.105522"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2023.1133060"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2020.105834"},{"key":"ref13","article-title":"Crop pest classification based on deep convolutional\n                        neural network and transfer learning","volume":"164","author":"Thenmozhi","year":"2019","journal-title":"Comput. Electron. Agricult."},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2017.08.005"},{"key":"ref15","article-title":"Citrus pests classification using an ensemble of deep\n                        learning models","volume":"186","author":"Khanramaki","year":"2021","journal-title":"Comput. Electron.\n                        Agricult."},{"key":"ref16","article-title":"Chinese agricultural diseases and pests named entity\n                        recognition with multi-scale local context features and self-attention\n                        mechanism","volume":"179","author":"Guo","year":"2020","journal-title":"Comput. Electron.\n                        Agricult."},{"key":"ref17","article-title":"Identification of stored grain pests by modified\n                        residual network","volume":"182","author":"Zhang","year":"2021","journal-title":"Comput. Electron.\n                        Agricult."},{"key":"ref18","first-page":"1","article-title":"Identification of navel orange diseases and pests\n                        based on the fusion of DenseNet and self-attention\n                    mechanism","volume":"2021","author":"Zhang","year":"2021","journal-title":"Comput. Intell. Neurosci."},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2991552"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3024891"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3390\/app12094356"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-16680-4"},{"key":"ref23","article-title":"Crop pest recognition in real agricultural\n                        environment using convolutional neural networks by a parallel attention\n                        mechanism","volume":"13","author":"Zhao","year":"2022","journal-title":"Frontiers Plant Sci."},{"key":"ref24","article-title":"Detection and classification of soybean pests using\n                        deep learning with UAV images","volume":"179","author":"Tetila","year":"2020","journal-title":"Comput.\n                        Electron. Agricult."},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2020.105809"},{"key":"ref26","article-title":"IoT-based pest detection and classification using\n                        deep features with enhanced deep learning\n                    strategies","volume":"121","author":"Prasath","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref27","first-page":"1","article-title":"Recognition of plant leaf diseases based on computer\n                        vision","author":"Nanehkaran","year":"2020","journal-title":"J. Ambient Intell. Humanized\n                        Comput."},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-022-04334-6"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2016.90"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d16-1244"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"issue":"10","key":"ref32","doi-asserted-by":"crossref","first-page":"4291","DOI":"10.1109\/TNNLS.2020.3019893","article-title":"Attention in natural language\n                        processing","volume":"32","author":"Galassi","year":"2021","journal-title":"IEEE Trans.\n                        Neural Netw. Learn. Syst."},{"key":"ref33","article-title":"Attention-based models for speech\n                        recognition","volume-title":"Proc. Adv. Neural Inf.\n                        Process. Syst.","volume":"28","author":"Chorowski"},{"key":"ref34","article-title":"Crop leaf disease recognition based on self-attention\n                        convolutional neural network","volume":"172","author":"Zeng","year":"2020","journal-title":"Comput.\n                        Electron. Agricult."},{"key":"ref35","volume-title":"Pest Dataset","year":"2023"},{"key":"ref36","article-title":"Very deep convolutional networks for large-scale\n                        image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref38","first-page":"2261","article-title":"Densely connected convolutional\n                        networks","volume-title":"Proc. IEEE\n                        Conf. Comput. Vis. Pattern Recognit. (CVPR)","author":"Huang"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref40","article-title":"MobileNets: Efficient convolutional neural networks\n                        for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2938194"},{"issue":"3","key":"ref43","doi-asserted-by":"crossref","first-page":"567","DOI":"10.3390\/agriculture13030567","article-title":"An effective pyramid neural network based on\n                        graph-related attentions structure for fine-grained disease and pest\n                        identification in intelligent agriculture","volume":"13","author":"Lin","year":"2023","journal-title":"Agriculture"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10380310\/10382486.pdf?arnumber=10382486","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,2]],"date-time":"2025-04-02T08:11:18Z","timestamp":1743581478000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10382486\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3351003","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}