AuroraWong

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《信息安全原理和实践》中学习到的加密算法

607prototxt

A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG

In this project, we propose a CNN model to classify single-channel EEG for driver drowsiness detection. We use the Class Activation Map (CAM) method for visualization. Results show that the model not only has a high accuracy but also learns biologically explainable features, e.g., Alpha spindles and Theta burst, as evidence for the drowsy state.

activityrecognition

Resources about activity recognition-行为识别资料

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

connectomemapper3

Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.

Coursera-ML-AndrewNg-Notes

吴恩达老师的机器学习课程个人笔记

Data-Science-Notes

数据科学的笔记以及资料搜集

Deep-BCI

An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning

iprs

Python Library for Radar Signal Intelligent Processing.

AuroraWong/-

《信息安全原理和实践》中学习到的加密算法

AuroraWong/607prototxt

AuroraWong/A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG

In this project, we propose a CNN model to classify single-channel EEG for driver drowsiness detection. We use the Class Activation Map (CAM) method for visualization. Results show that the model not only has a high accuracy but also learns biologically explainable features, e.g., Alpha spindles and Theta burst, as evidence for the drowsy state.

AuroraWong/activityrecognition

Resources about activity recognition-行为识别资料

AuroraWong/adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

AuroraWong/connectomemapper3

Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.

AuroraWong/Coursera-ML-AndrewNg-Notes

吴恩达老师的机器学习课程个人笔记

AuroraWong/Data-Science-Notes

数据科学的笔记以及资料搜集

AuroraWong/Deep-BCI

An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning

AuroraWong/iprs

Python Library for Radar Signal Intelligent Processing.

AuroraWong/keras-yolo4

A Keras implementation of YOLOv4 (Tensorflow backend)

AuroraWong/Machine-Learning

AuroraWong/meta-learning

meta-learning research

AuroraWong/multi-task-cnn-eeg-emotion

Code for the paper "Multi-Task CNN Model for Emotion Recognition from EEG Brain Maps". DEAP dataset. Python/Keras/Tensorflow 2 Impementation.

AuroraWong/radar-reconstruction-features-extraction

A signal reconstruction routine and a feature extraction routine used in radar processing.

AuroraWong/Significant-Preprocessing-Method-In-EEG-Based-Emotion-Classification

EEG preprocessing methods for classifying person emotions have been widely applied. However, there still remain some parts where determining significant preprocessing method can be improved.

AuroraWong/Virgilio

Your new Mentor for Data Science E-Learning.

AuroraWong/XJTU-Share

西安交通大学课程资料共享计划

AuroraWong/yr5-computational-intelligence

all useful material for ci unit