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  • Erlangen, Germany

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Fh-Hosseini/README.md

Hi, I'm Fatemeh (Farnoosh) Hosseini 👋

I'm a Master's student in Artificial Intelligence at FAU Erlangen-Nürnberg, writing my thesis at the Pattern Recognition Lab on reconstruction-based anomaly detection with deep generative models on large-scale 3D CT data.**.

🔭 Currently working on

  • Master's thesis: unsupervised anomaly detection on 3D CT volumes, moving through a family of generative architectures (AE → VAE → VQ-VAE → diffusion models), trained on HPC cluster

🧠 Research interests

  • Deep generative models (diffusion models, VAEs, VQ-VAEs)
  • Unsupervised anomaly detection & representation learning
  • 3D vision and volumetric data
  • Generative world models, video generation & multimodal systems
  • Efficient deep learning (making large models smaller and faster)
  • Applications: industrial inspection, medical imaging, and beyond

🛠️ Tools

Python · PyTorch · NumPy · OpenCV · scikit-learn · Slurm/HPC · Git · Conda

⭐️ Feel free to explore my repositories, and reach out if you'd like to talk about generative models, anomaly detection, or PhD opportunities.

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  1. computer-vision-master-projects computer-vision-master-projects Public

    A collection of five advanced computer vision projects, from classical geometry to face recognition and object detection, completed during my Master's program.

    Jupyter Notebook

  2. ct-anomaly-detection ct-anomaly-detection Public

    Master's thesis: reconstruction-based anomaly detection with deep generative models on large-scale 3D chest CT (CT-RATE-AD)

    Jupyter Notebook

  3. mnist-anomaly-detection mnist-anomaly-detection Public

    Reconstruction-based anomaly detection using a Convolutional Autoencoder on MNIST

    Python

  4. onset-detection-differentiable-spectral-flux onset-detection-differentiable-spectral-flux Public

    A classical spectral-flux onset detector reimplemented as a fully differentiable neural network.

    Jupyter Notebook