charan388

CNN-LSTM-EEG

A hybrid CNN-LSTM model is trained to localise anomalies in each channel of EEG record. Proposed architecture is divided into two steps. First, Deep CNN is trained for detecting abnormal channels. Furthermore, to detect anomaly time from abnormal channels Long Short-Term Memory (LSTM) network is trained.

awesome-bci

Curated Collection of BCI resources

ECG_Object_Detection

Cardiac Disorder Classification Using SSD MobileNet V2 based Deep Neural Network Architecture

EEG_CLASSIFICATION

EEG_Classification_Deeplearning

EEG Signal Classification using LSTM on various datasets

EnTGAN

leetcode

LeetCode Problems' Solutions

python_programming_assing-1

secured-QRcode-

QRcode encrypted with data that can only decoded by the receivers .

SeizurePrediction

A CNN + LSTM architecture to predict seizure from EEG data

traits-of-autism-spectrum-disorder-detection-

detecting autism disorder traits using random forest classifier algorithm

wafer_mlops_docs

This repo contains docs and dataset associated with wafer mlops demo lecture

chicken_disease_clasification

codellama

Inference code for CodeLlama models

EEGwithRaspberryPI

Open-Source board for converting RaspberryPI to Brain-computer interface

evci

machine_learning_project

This is first machine learning project.

music_recomendation_using_face_emotions

An Integrated project work working on the basis of three phases: 1- Find mood from your Face(video Input) 2- Classification Of songs Basd on its lyrics 3- Youtube Crawling

PPT_DSA_ASIGNMENTS

ASSIGNMENT -1 ARRAYS

RGNN

The model for the paper "EEG-Based Emotion Recognition Using Regularized Graph Neural Networks"

Thyroid-Disease-Detection