CVAug 24, 2020
Strawberry Detection using Mixed Training on Simulated and Real Data
arXiv:2008.10236v1
Originality Synthesis-oriented
AI Analysis
This is an incremental improvement for agricultural object detection tasks where labeled data is limited.
The paper tackled strawberry detection in agriculture by using mixed training on simulated and real data to address data scarcity, resulting in slightly higher accuracy.
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.