Hybrid attention network for semantic segmentation

Yin Yang; Juan Yang; Ronggui Wang

doi:10.1117/12.2684643

19 October 2023 Hybrid attention network for semantic segmentation

Yin Yang, Juan Yang, Ronggui Wang

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127091B (2023) https://doi.org/10.1117/12.2684643
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

Deep neural networks have made significant improvements in pixel-level semantic segmentation. However, the existing semantic segmentation algorithm still faces the problem of weighing between the accuracy and calculation cost of the segmentation. In response to this issue, this article proposes a hybrid network structure (HAM), looking for a balance point in the calculation accuracy and calculation speed. In this method, we construct a dual-attention module. The role of this module is to guide high -level characteristics through underlying characteristics to obtain more context information. Among them, the shape flow branch retains low-level space details, and semantic flow branches capture senior context information. These two branches are fused to strengthen information dissemination between different levels, thereby achieving higher segmentation accuracy. Experiments on the dataset show that this method achieves higher accuracy and speed under relatively small parameters. Compared with other real-time semantic segmentation methods, our network has achieved good compromise between parameters, speed, and accuracy.

Citation Download Citation

Yin Yang, Juan Yang, and Ronggui Wang "Hybrid attention network for semantic segmentation", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127091B (19 October 2023); https://doi.org/10.1117/12.2684643

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KEYWORDS

Image segmentation

Semantics

Convolution

Education and training

Performance modeling

Feature extraction

Image enhancement

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