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cani scanet.

Yuxuan Wan, Kaichen Zhou, jinhong Chen, Hao Dong
SCANet: Correcting LEGO Assembly Errors with Self-Correct Assembly Network
https://arxiv.org/abs/2403.18195

Yuxuan Wan, Kaichen Zhou, jinhong Chen, Hao Dong
SCANet: Correcting LEGO Assembly Errors with Self-Correct Assembly Network
https://arxiv.org/abs/2403.18195

Chunshi Wang, Bin Zhao, Shuxue Ding: SCANet: Split Coordinate Attention Network for Building Footprint Extraction https://arxiv.org/abs/2507.20809 https://arxiv.org/pdf/2507.20809 https://arxiv.org/html/2507.20809

complexity. SCANet-large (4.29M) achieves comparable accuracy to state-of-the-art methods with 70.9% fewer parameters. Meanwhile, SCANet-lite (90K) delivers 1390 fps in FP16, surpassing real-time standards. Additionally, we propose an efficient [4/5 of https://arxiv.org/abs/2504.14178v1]

model featuring Segregation and Context Aggregation Module (SCAM), which refines rough segmentation maps into weighted sky and cloud features processed separately. SCANet achieves state-of-the-art performance while drastically reducing computational [3/5 of https://arxiv.org/abs/2504.14178v1]

clouds from images for further feature analysis. Existing methods struggle to balance segmentation accuracy and computational efficiency, limiting real-world deployment on edge devices, so we introduce SCANet, a novel lightweight cloud segmentation [2/5 of https://arxiv.org/abs/2504.14178v1]

GRU-SCANET: Unleashing the Power of GRU-based Sinusoidal CApture Network for Precision-driven Named Entity Recognition https://www.biorxiv.org/content/10.1101/2024.12.04.626785v1

GRU-SCANET: Unleashing the Power of GRU-based Sinusoidal CApture Network for Precision-driven Named Entity Recognition https://www.biorxiv.org/content/10.1101/2024.12.04.626785v1

🧾 Source code, documentation, and implementation details available at:

GRU-SCANET introduces a GRU-based architecture integrating positional encoding, BiGRUs, multi-head attention, and a CRF decoder for biomedical NER.

🧠 Explore the latest from Bioinformatics Advances: "GRU-SCANET: Unleashing the Power of GRU-based Sinusoidal CApture Network for Precision-driven Named Entity Recognition" 

Full article available: https://doi.org/10.1093/bioadv/vbaf096