Multi-Scale Convolutions Meet Group Attention for Dense Prediction Tasks

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Multi-Scale Convolutions Meet Group Attention for Dense Prediction Tasks

Lecture Notes in Networks and Systems (LNNS,volume 882); The 13th Conference on Information Technology and Its Applications (CITA 2024) ; pp: 360-371.

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Détails bibliographiques
Auteurs principaux:	Vo, Xuan Thuy, Nguyen, Duy Linh, Priadana, Adri, Choi, Jehwan, Hyun Jo, Kang
Format:	Bài viết
Langue:	English
Publié:	Springer Nature 2024
Sujets:	Multi-Scale Convolutions Meet Group Attention for Dense Prediction Tasks On ImageNet-1K image classification, the proposed method achieves 77.6% Top-1 accuracy at 0.7 GFLOPs, surpassing other methods under similar computational costs
Accès en ligne:	https://elib.vku.udn.vn/handle/123456789/4293 https://doi.org/10.1007/978-3-031-74127-2_30
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Thư viện lưu trữ:	Trường Đại học Công nghệ Thông tin và Truyền thông Việt Hàn - Đại học Đà Nẵng

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Résumé:	Lecture Notes in Networks and Systems (LNNS,volume 882); The 13th Conference on Information Technology and Its Applications (CITA 2024) ; pp: 360-371.