In this paper, a novel flower detection application anchor-based method is proposed, which is combined with an attention mechanism to detect the flowers in a smart garden in AIoT more accurately and fast. While many researchers have paid much attention to the flower classification in existing studies, the issue of flower detection has been largely overlooked. The problem we have outlined deals largely with the study of a new design and application of flower detection. Firstly, a new end-to-end flower detection anchor-based method is inserted into the architecture of the network to make it more precious and fast and the loss function and attention mechanism are introduced into our model to suppress unimportant features. Secondly, our flower detection algorithms can be integrated into the mobile device. It is revealed that our flower detection method is very considerable through a series of investigations carried out. The detection accuracy of our method is similar to that of the state-of-the-art, and the detection speed is faster at the same time. It makes a major contribution to flower detection in computer vision.

中文翻译：

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使用移动设备基于YOLOv4的花朵端到端检测

本文提出了一种基于锚点的花卉检测应用新方法，该方法结合了一种关注机制，可以更加准确，快速地在AIoT智能花园中检测花朵。尽管许多研究人员在现有研究中已经非常关注花朵的分类，但是花朵检测的问题却被大大忽略了。我们概述的问题主要涉及花检测的新设计和应用的研究。首先，将一种新的基于端到端花朵检测锚的方法插入网络体系结构，使其更加珍贵和快速，并将损失函数和关注机制引入到我们的模型中以抑制不重要的特征。其次，我们的花朵检测算法可以集成到移动设备中。通过一系列的调查显示，我们的花朵检测方法非常重要。我们方法的检测精度与最新技术相似，并且检测速度更快。它为计算机视觉中的花朵检测做出了重要贡献。