Sonar Image-Based Fishery Fish School Density Retrieval Dataset
#image recognition #object detection #density estimation #fishery management #fish school monitoring #fisheries resource assessment
- 500 records
- 1.3G
- JPG
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
Currently, in the fisheries industry, accurate estimation of fish school density is crucial for resource management and fishery planning. However, traditional methods like manual observation and fishing records present issues of high cost, large error margins, and poor real-time performance. This dataset, based on sonar images, aims to enhance the accuracy and efficiency of fish detection, addressing the shortcomings of existing methods. Through this dataset, users can conduct image-based fish density analysis, achieving automated and precise fisheries resource management.The dataset is collected using sonar equipment in different fishery environments, with equipment installation depth and collection conditions carefully designed. Data quality is ensured through multiple rounds of labeling and review by a professional fisheries expert team, guaranteeing high precision and consistency. The labeling team comprises over 20 members with expertise in fisheries and image processing. Data preprocessing steps include noise filtering, image enhancement, and contrast adjustment, stored in JPG format, organized in categorized folders for easy retrieval and use.
Dataset Insights
Sample Examples
ce978780**.jpg|4284*5712|764.29 KB
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Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| fish_density | float | Estimated density of the fish school in the image. |
| school_count | int | The number of fish schools in the image. |
| fish_size_average | float | Average size of the fish in the school. |
| image_contrast | float | Contrast value of the sonar image. |
| reflection_intensity | float | Intensity of the sonar wave reflections on fish schools. |
| depth_measurement | float | Depth measurement where the fish school is located. |
| water_temperature | float | Water temperature at the time of image capture. |
| visibility | float | Underwater visibility during the capture of sonar images. |
| bottom_type | string | Type of bottom identified in the image such as mud, sand, or rock. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| 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 is the dataset for fish school density retrieval in fish farms based on sonar images?
- This dataset focuses on the analysis of fish school density using sonar images to accurately retrieve the density distribution of fish in farms.
- Which industry is this dataset primarily used for?
- This dataset is primarily used for the agriculture, forestry, and fisheries industry, specifically in research and applications in the fishing sector.
- What is the application value of the dataset?
- The use of sonar image analysis for fish school density can enhance fish farm management efficiency and the economic efficiency of fishing operations.
- How can sonar images be used to analyze fish school density?
- Sonar images detect the reflection signals from fish schools in the underwater environment, aiding in the analysis of the number and density of fish schools.
- What challenges might be faced when using this dataset?
- Processing sonar images may require complex signal processing techniques, and the analysis results need to be interpreted in the context of specific fish farm conditions.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Sonar Image-Based Fishery Fish School Density Retrieval Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/2f794ee85272b8ab0c19ac59018e332d},
urldate={2026-02-04},
keywords={sonar image, fishery fish school density, fish detection dataset, fisheries resource management},
version={1.0}
}Using this in research? Please cite us.
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