Update README.md

README.md

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 Each entry includes Subject_id, Age_group, Capture_Device, and lighting details for reproducible research.
 
+# Frequently Asked Questions
+
+## What capture devices are represented in the ear detection dataset?
+
+The ear detection dataset includes images captured with multiple devices, including a Canon R6 and an iPhone 15. This device diversity is useful when developing models intended for deployment across different cameras rather than a single imaging setup.
+
+## Does the dataset support recognition of both left and right ears?
+
+Yes. Each subject is represented by a full-face reference image together with multiple captures of both the left and right ear.
+
+## Who can benefit from this dataset?
+
+This dataset can benefit biometric researchers, computer-vision engineers, forensic technology teams, and developers building ear-based identification systems. Its combination of full-face images and multiple left- and right-ear images can support models that learn relationships between facial and ear characteristics. It is also useful for benchmarking ear detection and classification under different lighting, orientations, and capture conditions.
+
 ## 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/human-ear-detection-biometric-dataset/?utm_source=huggingface&utm_medium=referral&utm_campaign=ear-detection-dataset) to discuss your requirements and pricing options.
 
 Focused on advancing ear biometrics, the dataset enables studies on detection methods, feature extraction, and deep learning-based approaches.