Farmland Fence Detection Dataset

#object detection #object recognition #farmland management #intelligent agriculture #drone monitoring

5000 records
1.5G
JPG/PNG/JSON
CATL
MOBIUSI INC

Updated:2026-08-26

AI Analysis & Value Prop

The current agricultural industry faces challenges such as low efficiency in farmland management and difficulties in monitoring. Traditional manual inspection methods are not only time-consuming and labor-intensive but also prone to omissions. Existing monitoring solutions mostly rely on fixed cameras, which cannot adapt to the dynamic nature of farmland in real time, resulting in insufficient timeliness and accuracy of data. This dataset aims to help researchers and developers train efficient object detection models by providing a large number of farmland fence detection images, thereby enhancing the intelligence level of farmland monitoring. For data collection, drones are used to capture images of farmland fences under different times and weather conditions, ensuring diversity and comprehensiveness of the data. Quality control measures include multiple rounds of annotation and expert review to ensure consistency and accuracy of annotations. Data is stored with images in JPG format and annotations in JSON format, facilitating quick reading and processing.

Dataset Insights

Sample Examples

8e965556**.jpg|5184*3456|1.53 MB

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
fence_count	int	The total number of fences identified in the image.
fence_type	string	The type of fence, such as wooden fence, wire mesh, etc.
fence_material	string	The material used for the fence, such as wood, metal, etc.
fence_condition	string	The physical condition of the fence, such as intact, damaged, etc.
vegetation_coverage	float	The proportion of the area covered with vegetation in the image.
soil_type	string	The primary type of soil visible in the image.
weather_conditions	string	The weather conditions at the time the image was taken, such as sunny, cloudy, etc.
light_intensity	string	The intensity of light in the image, such as low, medium, high.
intrusion_status	string	Whether there are animals or humans intruding within the fenced area in the image.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What can this dataset be used for?: The farmland fence detection dataset can be used to develop and train object detection models in agriculture to achieve smart farmland management.

What types of image information are included in the dataset?: The dataset contains various images showing farmland fences from different perspectives and environments.

Why is this dataset important for the agriculture sector?: This dataset provides information on farmland boundaries, helping to improve the efficiency of agricultural resource management and promote precision agriculture.

How can this dataset be used to enhance smart farmland management?: By training object detection models, this dataset can be used to identify and monitor farmland boundaries, optimizing field planning and crop management.

Will the application of this dataset affect productivity?: Yes, using this dataset to develop object detection models can increase the automation of farmland management, thereby boosting productivity.

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Cite this Work

@dataset{Mobiusi2025,
  title={Farmland Fence Detection Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/3eb7912b1496d25ff8e2e74649ac4fa9?dataset_scene_id=5},
  urldate={2025-10-23},
  keywords={farmland fence detection, object detection dataset, agricultural intelligent monitoring, drone agriculture},
  version={1.0}
}

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