README.md

metadata

license: mit
tags:
  - remote-sensing
  - satellite-imagery
  - multi-label-classification
  - pytorch
  - efficientnetv2
  - mobilenetv2
datasets:
  - planet-understanding-the-amazon-from-space
metrics:
  - fbeta_score

🛰️ Planet Amazon Satellite Scene Multi-Label Classifier

Multi-label classification of remote sensing satellite images over the Amazon rainforest using MobileNetV2 (Baseline) and EfficientNetV2-S (Proposed Novel Architecture).

📊 Performance Benchmarks

• Dataset: Planet Amazon (40,479 images, 17 classes)
• Macro Recall: 98.72% (EfficientNetV2-S)
• Official Kaggle Public Score: 0.60475
• Official Kaggle Private Score: 0.59929 (Zero Overfitting, Δ = 0.0054)

🏗️ Architecture Innovations

• Backbone: EfficientNetV2-S with Fused-MBConv layers
• Loss: Label Smoothing Binary Cross-Entropy (ε = 0.05)
• Schedule: Cosine Annealing Learning Rate
• Activation: GELU non-linearities in 2-stage classification head