3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation

Research article (IEEE Transactions on Image Processing, 2019) · cited 190× · AI/ML
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3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation

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3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). 3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation. Retrieved May 24, 2026, from https://4ort.xyz/entity/3d2seqviews-aggregating-sequential-views-for-3d-global-feature-learning-by-cnn-with-hierarchical-attention-aggregation
MLA “3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/3d2seqviews-aggregating-sequential-views-for-3d-global-feature-learning-by-cnn-with-hierarchical-attention-aggregation.
BibTeX @misc{4ortxyz_3d2seqviews-aggregating-sequential-views-for-3d-global-feature-learning-by-cnn-with-hierarchical-attention-aggregation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation}}, year = {2026}, url = {https://4ort.xyz/entity/3d2seqviews-aggregating-sequential-views-for-3d-global-feature-learning-by-cnn-with-hierarchical-attention-aggregation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): 3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation — https://4ort.xyz/entity/3d2seqviews-aggregating-sequential-views-for-3d-global-feature-learning-by-cnn-with-hierarchical-attention-aggregation (retrieved 2026-05-24)

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