ViT-SAPS: Detail-Aware Transformer for Mechanical Assembly Semantic Segmentation

Semantic segmentation of mechanical assembly images provides an effective way to monitor the assembly process and improve the product quality. Compared with other deep learning models, Transformer has advantages in modeling global context, and it has been widely applied in various computer vision ta...

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Veröffentlicht in:	IEEE access 2023-01, Vol.11, p.1-1
Hauptverfasser:	Dong, Haitao, Chen, Chengjun, Wang, Jinlei, Shen, Feixiang, Pang, Yong
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive algorithms Assembly Computer vision Context modeling Convolutional neural networks Decoding Deep learning Image segmentation Interpolation mechanical assembly monitoring Monitoring Patches (structures) Semantic segmentation Semantics Task analysis Transformers vision Transformer
Online-Zugang:	Volltext
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