注意力机制主要是为了学习一种高效的车辆再识别任务特征嵌入方法，通过训练

Attention mechanism is mainly to re-learn an efficient vehicle feature recognition tasks embedding method, the region of interest can be obtained by training the learning network depth. <br><br>Can be found, most of the attention-based model will focus concentrated on the part of the region, when a vehicle when the image background is too complex will cause poor results.

The main purpose of the attention mechanism is to learn an efficient method of vehicle re-identification task feature embedding, which can obtain areas of interest by training deep learning networks.<br><br>It can be found that most attention-based models focus attention on some areas and can lead to poor results when the vehicle image background is too complex.

The main purpose of attention mechanism is to learn an efficient method of vehicle recognition task feature embedding, through the training of deep learning network, the region of interest can be obtained.<br>It can be found that most attention based models focus on some areas, which will lead to poor results when the background of vehicle image is too complex.<br>