Intel Image Classifier

GPU-accelerated transfer-learning pipeline with Optuna tuning and W&B logging.

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Domain
Deep Learning
Year
2025
Type
Applied build — internal engineering work

This is internal engineering and R&D work, not a client project. It is published to show technical depth — the modelling, evaluation, and tooling behind the AI automation we build for clients. No client is associated with it.

A high-performance image-classification pipeline on Intel's scene dataset (6 terrain classes: buildings, forest, glacier, mountain, sea, street). It leverages PyTorch Lightning, transfer learning, and experiment tracking with Weights & Biases for scalable, reproducible training.

Tools & methods

  • PyTorch Lightning
  • Optuna
  • Weights & Biases
  • ResNet18 / EfficientNet-B0
Full technical report

Objectives

  • Classify scene images into 6 terrain classes via transfer learning.
  • Optimize backbone architecture and learning rate with Optuna.
  • Log and visualize training metrics; deploy a modular, scalable pipeline.

Process

  • Download the Intel dataset via Kaggle API; organize into train/test/predict.
  • Build a Lightning DataModule to abstract loading.
  • Automate model tuning with Optuna across trials; log to W&B.
  • Select the best model, retrain, and evaluate on unseen data.

Results

  • Best model: EfficientNet-B0 with ~92% test accuracy after Optuna tuning.
  • Dashboards provided actionable visualizations of performance trends.

What we took from it

  • Optuna-tuned hyperparameters lifted accuracy in just a few trials.
  • Good infrastructure (Lightning + W&B) makes training reproducible and simple.

From the report

  • Intel Image Classifier overview
    Intel Image Classifier overview

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Client engagements

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    3 services
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    Ophir Jewellery ERP

    An ERP for a jewellery operation that brings product records, stock, customer activity, order handling, and business reporting into one calmer working view.

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    Live jewellery ERP available at ophir.eaquirstech.com.

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    Turner 10 Real Estate ERP

    A real-estate ERP that gives the team one practical place to follow properties, enquiries, availability, client records, and the internal work that supports every deal.

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    • NestJS
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    Live real-estate ERP available at turner10.eaquirstech.com.

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    • NestJS
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Engineering & AI R&D

This is internal and academic engineering work. Each study includes its full technical report.

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