High-Frequency Connector Detection Dataset
#Object Detection #Image Classification #Quality Inspection #Manufacturing #5G Device Testing
- 20000 records
- 3.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-09-21
AI Analysis & Value Prop
In the current industrial landscape, the rapid integration of 5G technology poses significant challenges in quality control, specifically in high-frequency connector testing. Existing solutions often lack accuracy and efficiency, leading to increased production costs and time delays. This dataset aims to address these technical challenges by providing a comprehensive collection of images from high-frequency connector inspections, facilitating the development of advanced quality assessment algorithms. The data is collected using high-resolution cameras in a controlled environment, ensuring consistent lighting and background. Rigorous quality control measures, including multi-round annotations and expert reviews, are implemented to maintain high standards of data integrity. The dataset is stored in JPG format, organized by categories based on inspection results.
Dataset Insights
Sample Examples
9248e0b9**.png|1932*1500|2.31 MB
43bf4dcd**.png|897*1500|617.21 KB
f5a6afba**.png|2004*1500|1.96 MB
cd4e9c49**.png|1333*1500|1.15 MB
9640ba85**.png|2237*1500|1.65 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| connector_type | string | Used to identify the specific type of high-frequency connector. |
| defect_type | string | Types of defects in the connector, such as scratches or cracks. |
| defect_severity | string | Description of the severity of the defect, such as minor or major. |
| defect_location | string | The specific location of the defect in the connector. |
| manufacturing_origin | string | The manufacturer or production line of the connector. |
| inspection_type | string | The method or technology used to perform detection, such as automatic or manual. |
| surface_condition | string | The overall condition of the connector's surface, such as smooth or uneven. |
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 is the High-Frequency Connector Detection Dataset?
- The High-Frequency Connector Detection Dataset is an object detection dataset used for quality inspection of 5G devices and high-speed modules, containing a large amount of image data to support quality inspection tasks.
- Which industry sectors is this dataset suitable for?
- This dataset is primarily used in the industrial sector, especially for quality inspection related to 5G devices and high-speed modules.
- What is the main purpose of the dataset?
- The main purpose of the dataset is to develop and evaluate automated object detection systems to increase the efficiency of quality inspection for 5G devices and high-speed modules.
- How does the image modality help in object detection?
- The image modality provides visual data that assists detection algorithms in identifying and classifying high-frequency connectors and their potential defects or issues.
- Why is this dataset critical for the inspection of 5G devices?
- Since 5G devices require high precision and reliability, the detection of high-frequency connectors can ensure these standards, thereby enhancing the overall performance and safety of the devices.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={High-Frequency Connector Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/0e279653508fd869ed9c98f936c2e0cd},
urldate={2025-08-28},
keywords={High-Frequency Connector Dataset,Industrial Quality Inspection,5G Device Testing,Image Data for Machine Learning},
version={1.0}
}Using this in research? Please cite us.
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