基于模拟和真实数据的混合训练的草莓检测
Strawberry Detection using Mixed Training on Simulated and Real Data
摘要:
本文展示了模拟图像如何在农业领域的目标检测任务中发挥作用,在农业领域,标记数据可能稀缺且收集成本高。我们考虑在真实图像中的草莓检测中使用真实和模拟数据的混合数据集进行训练。我们的研究结果表明,使用模拟数据集增强的真实数据集导致精度略高。
英文摘要:
This paper demonstrates how simulated images can be useful for object detection tasks in the agricultural sector, where labeled data can be scarce and costly to collect. We consider training on mixed datasets with real and simulated data for strawberry detection in real images. Our results show that using the real dataset augmented by the simulated dataset resulted in slightly higher accuracy.
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