πŸ›©οΈ Aircraft Classification Model

This model is based on DenseNet201 architecture, fine-tuned on the FGVC Aircraft (10,000 images) dataset.
It can classify aircraft into different variants with high accuracy.


πŸ“š Dataset

  • Name: FGVC Aircraft Dataset
  • Images: 10,000+
  • Source: FGVC Aircraft

πŸ—οΈ Model Architecture

  • Base Model: DenseNet201 (pre-trained on ImageNet)

  • Custom Layers:

    • GlobalAveragePooling2D
    • Dense(1024) + Mish activation + BatchNorm + Dropout
    • Dense(512) + Mish activation + BatchNorm + Dropout
    • Final Dense layer with Softmax activation
  • Optimizer: Adam

  • Learning Rate Schedule: CosineDecay

  • Batch Size: 8

  • Epochs: 50


πŸ“ˆ Performance

  • Achieved high validation accuracy.
  • Used EarlyStopping, ReduceLROnPlateau, and ModelCheckpoint for optimal training.

πŸ› οΈ How to Use

import tensorflow as tf

# Load the model
model = tf.keras.models.load_model('aircraft_model_finetuned.h5', custom_objects={"mish": mish})

# Predict
prediction = model.predict(preprocessed_image)
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