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README.md

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+---
+tags:
+- image classification
+- model training
+- medical assistance
+- elderly care
+- rehabilitation
+license: cc-by-nc-sa-4.0
+task_categories:
+- image-classification
+language:
+- en
+pretty_name: Electric Wheelchair Model Classification Image Dataset
+size_categories:
+- 1B<n<10B
+---
+
+# Electric Wheelchair Model Classification Image Dataset
+
+In the current medical industry, the use of electric wheelchairs is increasingly popular, especially in elderly care and rehabilitation. However, existing methods for classifying electric wheelchairs often rely on manual labeling, which is inefficient and prone to errors. Current solutions often cannot provide efficient, accurate classification support, leading to resource waste and poor patient experience. This dataset aims to provide high-quality electric wheelchair image data to support automated image classification tasks, thereby improving classification accuracy and efficiency. Data collection uses professional photography equipment to capture different models of electric wheelchairs in a natural light environment, ensuring image quality. For quality control, multiple rounds of labeling and consistency checks are employed to ensure accurate labeling of each image. The data is stored in JPG format, organized by category for easy retrieval and use.
+
+## Technical Specifications
+
+| Field | Type | Description |
+| :---  | :---  | :--- |
+| file_name | string | File name |
+| quality | string | Resolution |
+| color | string | The exterior color of the electric wheelchair. |
+| wheel_type | string | Type of wheels equipped on the electric wheelchair. |
+| seat_material | string | Material used for the seat of the electric wheelchair. |
+| control_interface_type | string | Type of interface used to control the electric wheelchair. |
+
+## Compliance Statement
+
+<table>
+  <tr>
+    <td>Authorization Type</td>
+    <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
+  </tr>
+  <tr>
+    <td>Commercial Use</td>
+    <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
+  </tr>
+  <tr>
+    <td>Privacy and Anonymization</td>
+    <td>No PII, no real company names, simulated scenarios follow industry standards</td>
+  </tr>
+  <tr>
+    <td>Compliance System</td>
+    <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
+  </tr>
+</table>
+
+## Source & Contact
+
+If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/c6eaa4f91ab82cce1c50ec89e9fa41d9?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com