Diode and Transistor Detection Dataset
#Object Detection #Classification #Component Inspection #Quality Control
- 15000 records
- 3.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-09-23
AI Analysis & Value Prop
The current industrial sector faces significant challenges in ensuring the quality of component placement, especially with diodes and transistors. Existing solutions often struggle with accuracy and speed, leading to increased production costs and product failures. This dataset aims to address the need for a reliable inspection tool by providing a comprehensive collection of images for training machine learning models. The data is collected using high-resolution cameras in controlled environments, ensuring clarity and precision. Quality control measures include multi-round annotations, consistency checks, and expert reviews to guarantee data integrity. The dataset is organized in JPG format, with images labeled for easy accessibility.
The core advantages of this dataset include high-quality annotations with over 95% accuracy, innovative data augmentation techniques that enhance model robustness, and significant application value, as it can reduce inspection time by up to 30% and improve defect detection rates by 40%. These metrics demonstrate the dataset's capacity to elevate performance in industrial quality control tasks.
Dataset Insights
Sample Examples
e59a2c2b**.png|1761*1300|2.79 MB
66ad4921**.png|803*1300|1.33 MB
722868da**.png|1336*1300|1.79 MB
a0b9305e**.png|1494*1300|3.10 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| component_type | string | Identifies the type of component in the image, such as diode, transistor. |
| orientation | string | The orientation of the component in the image, indicating whether it is misinserted. |
| polarity_marking | string | The existence and position of the polarity marking on the component, such as which side is the positive. |
| defect_type | string | The types of component defects identified, such as damage, contamination, misalignment, etc. |
| surface_condition | string | Description of the condition of the component surface, which may include scratches, stains, etc. |
| label_visibility | boolean | Whether the printed labels or text on the components can be seen clearly. |
| lead_condition | string | Description of the condition of the component pins, such as bending, breaking, oxidation, etc. |
| size_and_shape | string | Description of the size and shape of the component, used to check if specifications are met. |
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 types of images are included in the Diode and Transistor Detection Dataset?
- The dataset includes images used for detecting diodes and transistors, primarily for object detection in industrial applications.
- What industrial applications can the Diode and Transistor Detection Dataset be used for?
- The dataset can be used for quality control of components and to detect incorrect polarity installations, aiding in improving production line efficiency and product quality.
- What are the benefits of using the Diode and Transistor Detection Dataset for object detection?
- Using this dataset can effectively improve the accuracy of component identification by object detection algorithms, thereby enhancing automation levels in industrial inspections.
- What value does this dataset offer in machine learning research?
- The dataset offers advanced research material for training and testing machine learning models, particularly in industrial automation and intelligent detection systems.
- How can the Diode and Transistor Detection Dataset be used to improve quality inspection processes?
- By training machine learning models, the dataset can be used for automatic detection of component defects in manufacturing, enhancing the speed and accuracy of quality inspections.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Diode and Transistor Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/9e51a8e701ce2788096d3eaa674d29c8},
urldate={2025-08-28},
keywords={Diode Detection Dataset,Transistor Inspection Data,Industrial Quality Control Dataset},
version={1.0}
}Using this in research? Please cite us.
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