lwlBCI
Undergraduate and master studies at the North University of China, as for the interpretability of EEG signal decoding and cognitive neuroscience
Taiyuan, China
Pinned Repositories
About-EEG
Try to do some research on EEG signal decoding
AIGC-Brain
Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy
Awesome-Evaluation-of-Visual-Generation
A list of works on evaluation of visual generation models, including evaluation metrics, models, and systems
CVPR2024-Papers-with-Code
CVPR 2024 论文和开源项目合集
EEG-Decoding
脑电信号解码的真实证据
EEG-Decoding-Cognition
关于一篇经典的---认知任务量的深度学习解码方法
EEG-MI-ATCNet
运动想象分类模型---ATCNet，源代码融合了关于EEGNet,DeepConvNet,ShallowConvNet等多种典型模型作对比
EEG2Image
EEG2IMAGE: Image Reconstruction from EEG Brain Signals. [ICASSP 2023]
ER-4D-CRNN
使用4D切片方式，利用深度学习从时、频、空间域进行EEG情绪识别解码
neural_speech_decoding
lwlBCI's Repositories
lwlBCI/EEG-MI-ATCNet
运动想象分类模型---ATCNet，源代码融合了关于EEGNet,DeepConvNet,ShallowConvNet等多种典型模型作对比
lwlBCI/ER-4D-CRNN
使用4D切片方式，利用深度学习从时、频、空间域进行EEG情绪识别解码
lwlBCI/About-EEG
Try to do some research on EEG signal decoding
lwlBCI/EEG-Decoding
脑电信号解码的真实证据
lwlBCI/EEG-Decoding-Cognition
关于一篇经典的---认知任务量的深度学习解码方法
lwlBCI/EEG2Image
EEG2IMAGE: Image Reconstruction from EEG Brain Signals. [ICASSP 2023]
lwlBCI/neural_speech_decoding
lwlBCI/AIGC-Brain
Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy
lwlBCI/Awesome-Evaluation-of-Visual-Generation
A list of works on evaluation of visual generation models, including evaluation metrics, models, and systems
lwlBCI/CVPR2024-Papers-with-Code
CVPR 2024 论文和开源项目合集
lwlBCI/github-readme-stats
:zap: Dynamically generated stats for your github readmes
lwlBCI/lwlBCI
about me
lwlBCI/Picgoo
用于显示图像
lwlBCI/EEG-DL
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
lwlBCI/EEG-Image-Reconstruction
Image reconstruction from visual evoked potentials using latent diffusion
lwlBCI/EEG_emotion_recognition
硕士期间课题研究记录
lwlBCI/External-Attention-pytorch
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
lwlBCI/Grad-CAM.pytorch
pytorch实现Grad-CAM和Grad-CAM++,可以可视化任意分类网络的Class Activation Map (CAM)图,包括自定义的网络;同时也实现了目标检测faster r-cnn和retinanet两个网络的CAM图;欢迎试用、关注并反馈问题...
lwlBCI/MindEyeV2
brilliant！