SIPPRE Group Software Repository

The SIPPRE Group actively contributes to open-source research and development by sharing tools, software, and educational projects through our GitHub repositories. These resources are categorized into student projects, research-specific tools, and organizational repositories dedicated to advanced topics in Brain Signal Processing and Medical Image Analysis.

Student Projects

We encourage undergraduate students to participate in hands-on projects that merge theory with practical implementation. These projects often explore innovative ideas in areas such as EEG analysis, sound and speech processing, and data analysis. Examples of recent student projects include:

  • Exploring how binaural sounds affect brain rhythms using EEG: Analysis of EEG signals related to binaural sound processing.
  • Developing an Emotion Based Music Playlist: A platform that curates playlists based on user emotional states.
  • Developing an AI Tourist Guide: An AI-powered application designed to offer personalized tour guidance.
  • Exploratory Data Analysis of Users’ Spotify Listening Preferences: Analysis of user preferences on Spotify using Exploratory Data Analysis techniques.
  • Heart Murmur Recognition: A medical-focused project detecting murmurs in heart sounds.
  • Greek Traditional Music Emotion Analysis and Recognition: Recognizing emotions in traditional Greek music using Jupyter Notebook-based workflows.

Our student repositories highlight the innovative spirit of our lab and serve as an incubator for future researchers.

Organizational Repositories

We maintain two key GitHub organizations for structured and specialized research contributions:

Brain Signal Processing Group (BSPG):
This repository focuses on advanced EEG analysis, BCI development, and signal processing tools.

  • A Real time Brain Computer Interface System: Control of robotic vehicles via brain activity.
  • Brain Rhythm analysis during listening to music using Enophones: Recording EEG signals while listening to music using Enophones.
  • An experimental protocol for BCI applications: Demonstrating the foundational concepts of brain-computer interface applications.

Digital Mammography Research Group (DigMammo):

Dedicated to medical image analysis, this organization shares tools and datasets for developing cutting-edge solutions in breast cancer detection.

  • CBIS-DDSM_CNNs: Deep learning-based CNN implementations for breast mass detection.
  • CBISDDSM_Mass_Detection: Python-based tools for automating mass detection in mammograms.

Research and Development Tools

Our software tools extend beyond these repositories and focus on the following areas:

  • Brain-Computer Interfaces (BCI): EEG signal analysis tools, real-time feedback mechanisms, and experimental protocols for BCI applications.
  • Medical Imaging: Deep learning frameworks and specialized algorithms for segmentation, anomaly detection, and GAN-driven imaging transformations.
  • Sound and Speech Processing: Algorithms for emotion recognition, acoustic modeling, and speech signal enhancement.

You can explore our GitHub page for the latest tools and contributions, including projects on:

  • EEG signal processing with MNE Tools and EEGLAB.
  • Image recognition using OpenCV and deep learning with TensorFlow, PyTorch, and Keras.
  • Sound and speech signal analysis with NVIDIA Riva, OpenSmile, and Librosa.

Our repositories reflect our open-source philosophy, promoting collaboration and innovation in signal and image processing. Whether you are a researcher, student, or enthusiast, the SIPPRE GitHub resources are a gateway to cutting-edge research and practical tools.

You can follow the group’s software and tools updates in our software repositories in github: