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Article summary:

1. A YOLOV5 model implanted with a transformer module is used to achieve accurate online identification for cabbage fields under complex environments.

2. An NVIDIA Jetson Xavier NX is used to build a new target-oriented spray system.

3. The experimental results indicate that the average precision is 98.65%, and the savings rate reaches 54.04%.

Article analysis:

The article provides an overview of the design and experimental verification of the YOLOV5 model implanted with a transformer module for target-oriented spraying in cabbage farming, which appears to be reliable and trustworthy. The authors provide evidence from both indoor tests and field experiments, which demonstrate that the system achieves its expected results with an average precision of 96.14% indoors and 98.65% outdoors, as well as a savings rate of 54.04%. However, there are some potential biases in the article that should be noted. For example, it does not explore any counterarguments or present both sides equally; instead, it focuses solely on the benefits of using this system for target-oriented spraying in cabbage farming without considering any potential risks or drawbacks associated with its use. Additionally, there is no mention of any other methods or systems that could be used for this purpose, so it is unclear whether this system is truly superior to other options available on the market today. Finally, there is no discussion of how much this system would cost to implement or maintain over time, which could be important information for potential users who are considering investing in such a system for their own operations.