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FINE-GRAINED IMAGE RECOGNITION METHOD, ELECTRONIC DEVICE AND STORAGE MEDIUM

机译:细粒度图像识别方法,电子设备和存储介质

摘要

The present disclosure provides a fine-grained image recognition method, an electronic device and a computer readable storage medium. The method comprises the steps of feature extraction, calculation of feature discriminant loss function, calculation of feature diversity loss function and calculation of model optimization loss function. The present disclosure comprehensively considers influences of factors such as a large intra-class difference, a small inter-class difference, and a great influence of background noise of the fine-grained image, and makes constrains such that the feature maps belonging to each class are discriminative and have the features of corresponding class, thus reducing the intra-class difference, decreasing the learning difficulty and learning better discriminative features. The constraints make the feature maps belonging to each class have a diversity, which increases the inter-class difference, achieves a good result, and is easy for practical deployment, thereby obviously improving the effect of multiple fine-grained image classification tasks.
机译:本公开提供了一种细粒度的图像识别方法,电子设备和计算机可读存储介质。该方法包括特征提取的步骤,特征判别损失函数的计算,特征分集丢失函数的计算和模型优化损失函数的计算。本揭露全面考虑了大量级别差异,小型阶级差异的因素的影响,以及细粒度图像的背景噪声的巨大影响,使得属于每个类的特征映射是歧视性的并且具有相应阶级的特征,从而减少了阶级差异,降低了学习难度和学习更好的歧视特征。约束使属于每个类的特征映射具有多样性,这增加了阶级差异,实现了良好的结果,并且易于实际部署,从而显然提高了多个细粒度图像分类任务的效果。

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