efficientnet-b3-skin-classifier

EfficientNet-B3 Skin Disease Classifier

Overview

This repository provides an EfficientNet-B3 image classification model trained to recognize common skin diseases from clinical skin images.

The model is intended for research and educational purposes only and should not be used as a substitute for professional medical diagnosis.

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Model Architecture

• Backbone: EfficientNet-B3
• Framework: TensorFlow / Keras
• Task: Multi-class Image Classification

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Disease Classes

The model predicts one of the following classes:

• Eczema
• ACD
• Psoriasis
• Tinea
• Urticaria
• Folliculitis
• Insect Bite
• Acne

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Dataset

The model was trained using a custom dataset constructed from the SCIN (Skin Condition Image Network) dataset and DermNet images. The collected images were manually curated and mapped into eight diagnostic categories.

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Input

• RGB Image
• Image Size: 300 × 300 pixels

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Output

The model returns the probability for each disease class.

Example:

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Files

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Example

import tensorflow as tf

model = tf.keras.models.load_model("efficientnet_b3.keras")

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Intended Use

This model is designed for:

• Academic research
• Computer Vision experiments
• Medical AI education
• Prototype applications

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Limitations

• Not intended for clinical diagnosis.
• Performance depends on image quality.
• Predictions should always be interpreted by healthcare professionals.

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Author

Chantaro Ntw

AI Engineer | Computer Vision | Medical AI