{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:12:22Z","timestamp":1780636342707,"version":"3.54.1"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Science and Technology Development Fund of Macau SAR","award":["0141\/2023\/RIA2"],"award-info":[{"award-number":["0141\/2023\/RIA2"]}]},{"name":"Science and Technology Development Fund of Macau SAR","award":["0193\/2023\/RIA3"],"award-info":[{"award-number":["0193\/2023\/RIA3"]}]},{"name":"Key Areas Research and Development Program of Guangzhou","award":["2023B01J0029"],"award-info":[{"award-number":["2023B01J0029"]}]},{"name":"Guangdong Provincial Key Laboratory of Cyber-Physical System","award":["2020B1212060069"],"award-info":[{"award-number":["2020B1212060069"]}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2024A1515011729"],"award-info":[{"award-number":["2024A1515011729"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Development Fund, Macau SAR","award":["0141\/2023\/RIA2"],"award-info":[{"award-number":["0141\/2023\/RIA2"]}]},{"name":"Science and Technology Development Fund, Macau SAR","award":["0193\/2023\/RIA3"],"award-info":[{"award-number":["0193\/2023\/RIA3"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Consumer Electron."],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1109\/tce.2025.3571865","type":"journal-article","created":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T13:15:04Z","timestamp":1747746904000},"page":"2876-2891","source":"Crossref","is-referenced-by-count":1,"title":["IPGRN: An Integrated Progressive Gated Refinement Network for Breast Tumor Analysis"],"prefix":"10.1109","volume":"71","author":[{"given":"Zihao","family":"Dai","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3640-3229","authenticated-orcid":false,"given":"Guoheng","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9503-1441","authenticated-orcid":false,"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Shenzhen Polytechnic University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8919-5825","authenticated-orcid":false,"given":"Jianbin","family":"He","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7490-6695","authenticated-orcid":false,"given":"Xiaochen","family":"Yuan","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University, Macau, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1788-3746","authenticated-orcid":false,"given":"Chi-Man","family":"Pun","sequence":"additional","affiliation":[{"name":"Faculty of Science and Technology, University of Macau, Macau, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6428-5645","authenticated-orcid":false,"given":"Guo","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0633-7224","authenticated-orcid":false,"given":"Bingo Wing-Kuen","family":"Ling","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaopan","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2645-330X","authenticated-orcid":false,"given":"Jiao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2015.11.029"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2014.05.032"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.14569\/ijacsa.2020.0110702"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s41571-022-00707-0"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2022.08.149"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1186\/s40779-023-00458-8"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12041372"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.222729"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2023.3321331"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2024.3370310"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2023.3337234"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2023.3301874"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3016820"},{"key":"ref15","first-page":"10944","article-title":"What makes multi-modal learning better than single (provably)","volume-title":"Proc. Adv. neural inf. proces. syst. (NeurIPS)","author":"Huang"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2798607"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3408317"},{"key":"ref18","first-page":"1","article-title":"A kernel method for canonical correlation analysis","volume-title":"Proc. Math. Stat. IMPS","author":"Shotaro"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-4380-9_14"},{"key":"ref20","first-page":"1083","article-title":"On deep multi-view representation learning","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","volume":"37","author":"Wang"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3230750"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87237-3_51"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-23774-w"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3159264"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2738401"},{"key":"ref26","first-page":"2539","article-title":"Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis","volume-title":"Proc. Conf. Empir. Methods Nat. Lang. Process. (EMNLP)","author":"Poria"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/iccv48922.2021.00147"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/icassp40776.2020.9053762"},{"key":"ref29","first-page":"1513","article-title":"A variational information bottleneck approach to multi-omics data integration","volume-title":"Proc. Mach. Learn. Res. (AISTATS)","volume":"130","author":"Lee"},{"key":"ref30","first-page":"6558","article-title":"Multimodal transformer for unaligned multimodal language sequences","volume-title":"Proc. Annu. Meet. Assoc. Comput. Linguist.","author":"Tsai"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr42600.2020.01271"},{"key":"ref32","first-page":"1","article-title":"Trusted multi-view classification","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Han"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2012.6247814"},{"key":"ref34","first-page":"568","article-title":"Two-stream convolutional networks for action recognition in videos","volume-title":"Proc. Adv. Neural Inf. Proces. Syst. (NeurIPS)","author":"Simonyan"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/iccv.2019.00640"},{"key":"ref36","first-page":"6881","article-title":"Trustworthy multimodal regression with mixture of normal-inverse gamma distributions","volume-title":"Proc. Adv. Neural Inf. Proces. Syst. (NeurIPS)","author":"Ma"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197266"},{"key":"ref38","first-page":"3045","article-title":"The power of scale for parameter-efficient prompt tuning","volume-title":"Proc. Conf. Empir. Methods Nat. Lang. Process. (EMNLP)","author":"Lester"},{"key":"ref39","first-page":"4582","article-title":"Prefix-tuning: Optimizing continuous prompts for generation","volume-title":"Proc. Conf. Annu. Meet. Assoc. Comput. Linguist. (ACL)","author":"Li"},{"key":"ref40","first-page":"487","article-title":"AdapterFusion: Non-destructive task composition for transfer learning","volume-title":"Proc. Conf. Eur. Chapter Assoc. Comput. Linguist., Proc. Conf. (EACL)","author":"Pfeiffer"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CGiV.2016.61"},{"key":"ref42","first-page":"1405","article-title":"K-adapter: Infusing knowledge into pre-trained models with adapters","volume-title":"Proc. Find. Assoc. Comput. Linguist. (NAACL)","author":"Wang"},{"key":"ref43","first-page":"1","article-title":"LoRA: Low-rank adaptation of large language models","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Hu"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.00024"},{"key":"ref45","first-page":"37","volume-title":"Long Short-Term Memory","author":"Graves","year":"2012"},{"key":"ref46","first-page":"1243","article-title":"Learning to combine foveal glimpses with a third-order Boltzmann machine","volume-title":"Proc. Adv. Neural Inf. Proces. Syst. (NeurIPS)","author":"Larochelle"},{"key":"ref47","first-page":"2204","article-title":"Recurrent models of visual attention","volume-title":"Proc. Adv. Neural Inf. Proces. Syst. (NeurIPS)","author":"Mnih"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CyberneticsCom.2013.6865784"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr42600.2020.01181"},{"key":"ref50","first-page":"10353","article-title":"HorNet: Efficient high-order spatial interactions with recursive gated convolutions","volume-title":"Proc. Adv. neural inf. proces. syst. (NeurIPS)","volume":"35","author":"Rao"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2023.3284509"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-17-0339"},{"key":"ref53","first-page":"6450","article-title":"A closer look at spatiotemporal convolutions for action recognition","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Tran"},{"key":"ref54","article-title":"The Chinese mammography database (CMMD): An online mammography database with biopsy confirmed types for machine diagnosis of breast","volume":"1","author":"Cui","year":"2021","journal-title":"Cancer Imag. Arch."},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/2717454"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1038\/srep27327"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9622-7"},{"key":"ref58","first-page":"76","article-title":"From canonical correlation analysis to self-supervised graph neural networks","volume-title":"Proc. Adv. Neural Inf. Proces. Syst. (NeurIPS)","author":"Zhang"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-20-4935"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.02005"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25643"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2023.3253760"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s10579-008-9076-6"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1002\/hep.21563"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3286826"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9341165"}],"container-title":["IEEE Transactions on Consumer Electronics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/30\/11128999\/11007610.pdf?arnumber=11007610","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T17:36:53Z","timestamp":1760117813000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11007610\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":67,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tce.2025.3571865","relation":{},"ISSN":["0098-3063","1558-4127"],"issn-type":[{"value":"0098-3063","type":"print"},{"value":"1558-4127","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5]]}}}