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However, a solitary 2D or 3D CNN encounters challenges such as insufficiently extracting scattering channel dimension features or excessive computational parameters. Moreover, these networks\u2019 default is that all information is equally important, consuming vast resources for processing useless information. To address these issues, this study presents a new hybrid CV-CNN with the attention mechanism (CV-2D\/3D-CNN-AM) to classify PolSAR ground objects, possessing both excellent computational efficiency and feature extraction capability. In the proposed framework, multi-level discriminative features are extracted from preprocessed data through hybrid networks in the complex domain, along with a special attention block to filter the feature importance from both spatial and channel dimensions. Experimental results performed on three PolSAR datasets demonstrate our present approach\u2019s superiority over other existing ones. Furthermore, ablation experiments confirm the validity of each module, highlighting our model\u2019s robustness and effectiveness.<\/jats:p>","DOI":"10.3390\/rs16162908","type":"journal-article","created":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T07:59:07Z","timestamp":1723190347000},"page":"2908","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Complex-Valued 2D-3D Hybrid Convolutional Neural Network with Attention Mechanism for PolSAR Image Classification"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1108-0507","authenticated-orcid":false,"given":"Wenmei","family":"Li","sequence":"first","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7141-9170","authenticated-orcid":false,"given":"Hao","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiadong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhong","family":"He","sequence":"additional","affiliation":[{"name":"Department of Geography, Geomatics and Environment, University of Toronto, Mississauga, ON L5L 1C6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5520","DOI":"10.1109\/TGRS.2016.2567421","article-title":"The Impacts of Building Orientation on Polarimetric Orientation Angle Estimation and Model-Based Decomposition for Multilook Polarimetric SAR Data in Urban Areas","volume":"54","author":"Li","year":"2016","journal-title":"IEEE Trans. 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