This is our EE512 Machine Learning semester project at Department of ELectrical Engineering at ITU.
- Merging Data From Multiple Sources
- Initial Dataset Exploration
- Feature Extraction
- Extract More Features
- Train Test Split
- APPLY PCA
- Train Models
- Neural Network
- Convolutional Neural Network
- Isolation Forest (Anomaly Detection)
- OneClass SVM (Anomaly Detection)
- Autoencoders (Anomaly Detection)
Fawad Arshad (MSDS17001@itu.edu.pk)
Hazoor Ahmad (PHDEE17004@itu.edu.pk)
Jawad Arshad (MSDS17011@itu.edu.pk)
Zeeshan Haider (MSEE17001@itu.edu.pk)
Our models need librosa, along with other libraries imported at the top of every ipynb files.
You can make your own dataset of audios or use Google, Mivia or Kaggle dataset for gunshot detection. Your can aso download dataset from https://drive.google.com/drive/folders/1_H68GGKBqGsCxQVNZb8lxFy_apRUlhvF?usp=sharing
You can also write your own codes for the evaluation of our Trained Models.
Realtime simulation codes are also included.