中圖分類(lèi)號(hào)：TP391.41；TP18
文獻(xiàn)標(biāo)志碼：A
DOI: 10.16157/j.issn.0258-7998.233817
中文引用格式： 彭瑩瓊，俞融融，尹乘樂(lè)，等. 基于雙線性池化的實(shí)蠅分類(lèi)注意力網(wǎng)絡(luò)[J]. 電子技術(shù)應(yīng)用，2023，49(5)：8-13.
英文引用格式： Peng Yingqiong，Yu Rongrong，Ying Chengle，et al. Attention networks for fruit fly classification based on bilinear pooling[J]. Application of Electronic Technique，2023，49(5)：8-13.

Attention networks for fruit fly classification based on bilinear pooling

Abstract： Fruit fly is a kind of quarantine pest that attracts much attention at home and abroad. There are many kinds of fruit flies. Different kinds of fruit flies are similar in shape and size, which is difficult to identify. In addition, in practical applications, it is difficult to identify fruit flies due to the lack of information about shielding, view-point, changing light and shadow and other factors. This study proposes a bilinear pooled attention network for fruit fly classification to learn effective discriminant characteristics. The network is composed of two parts: saliency feature module and cross-layer bilinear feature module. Saliency feature module realizes feature enhancement by filtering enhancement processing of two different convolution layers. Cross-layer bilinear module is based on bilinear pooling fusion features, determines the attention location, and mines discriminant features. Experiments on fruit fly’s data set with natural environment background show that the method is effective and has good practical application prospect.

Key words : fruit fly detection；bilinear pooling；attention mechanism