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sumeyye-agac/README.md

Hi, I'm Sumeyye 👋

🏫 I earned my PhD in Computer Engineering from Bogazici University, Istanbul, Turkey 🎓. I'm passionate about machine learning and deep learning, with a particular focus on developing efficient AI solutions for wearable and mobile technologies ⌚ 🎧 📱. My work centers around optimizing resource usage while ensuring high-performance systems. On my profile, you'll find projects related to these areas, as well as a variety of other projects I've worked on 🌟.

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  1. har-phd-thesis har-phd-thesis Public

    Enhancing lightweight models for efficient sensor-based human activity recognition

    Python 1

  2. dreamcatcher-earable-wearer-aware-benchmark dreamcatcher-earable-wearer-aware-benchmark Public

    Resource-efficient wearer-aware event recognition on earables (DreamCatcher dataset)

    Jupyter Notebook 1

  3. awesome-efficient-har awesome-efficient-har Public

    An awesome list of papers, datasets, and tools for efficient sensor-based Human Activity Recognition (HAR), with a focus on lightweight and edge-friendly deep learning.

    Python 1

  4. wearable-edge-xrfv2-benchmark wearable-edge-xrfv2-benchmark Public

    Edge-first XRF V2 benchmark for deployable wearable event detection (earbuds + smart-glasses), with FP/hour-calibrated metrics and reproducible run artifacts.

    Python

  5. homography-and-image-stitching-from-scratch homography-and-image-stitching-from-scratch Public

    Implemention of a python program which can stitch input images together to create a single panoramic image, called blended image

    Python 11

  6. expectation-maximization-for-gaussian-mixture-model-from-scratch expectation-maximization-for-gaussian-mixture-model-from-scratch Public

    Expectation-Maximization (EM) algorithm for Gaussian mixture model (GMM) from scratch

    Python 4 1