classification of emotions using EEG signals with deep learning methods -- 2
Budget: $250 – $750 USD
1. Dataset: DEAP dataset
2. Convert 1D EEG to 2D images
Algorithm: using short time fourier transform (STFT) (output: spectrogram)
2. Classification using deep learning
a. Inception Resnet-V2 (link: https://drive.google.com/file/d/1OSxQ8mgji8zgqMHxWmQSSabR-GuEBJQN/view?usp=sharing)
b. DenseNet121 modified (link: https://drive.google.com/file/d/1KzZJPCffPNB3mtlZs4dglmwbkh_8iJu6/view?usp=sharing)
Notes: looking for someone who has worked on EEG or signal processing projects
2. Convert 1D EEG to 2D images
Algorithm: using short time fourier transform (STFT) (output: spectrogram)
2. Classification using deep learning
a. Inception Resnet-V2 (link: https://drive.google.com/file/d/1OSxQ8mgji8zgqMHxWmQSSabR-GuEBJQN/view?usp=sharing)
b. DenseNet121 modified (link: https://drive.google.com/file/d/1KzZJPCffPNB3mtlZs4dglmwbkh_8iJu6/view?usp=sharing)
Notes: looking for someone who has worked on EEG or signal processing projects