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wh28325's Projects

3ddfa_v2 icon 3ddfa_v2

The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.

ailearning icon ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

applied-ml icon applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

arl-eegmodels icon arl-eegmodels

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

bert icon bert

TensorFlow code and pre-trained models for BERT

bert-as-service icon bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

braindecode icon braindecode

Deep learning software to decode EEG or MEG signals

byol-pytorch icon byol-pytorch

Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch

cd-diagram icon cd-diagram

Critical difference diagram with Wilcoxon-Holm post-hoc analysis.

cnn-explainer icon cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.

confuse icon confuse

CONFUSE: CONVOLUTIONAL TRANSFORM LEARNING BASED MULTI-CHANNEL FUSION FRAMEWORK

deepeeg icon deepeeg

Deep Learning with Tensor Flow for EEG MNE Epoch Objects

deeplearning icon deeplearning

Python for《Deep Learning》,该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06

deepsleepnet icon deepsleepnet

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

detr icon detr

End-to-End Object Detection with Transformers

dgl icon dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dl-4-tsc icon dl-4-tsc

Deep Learning for Time Series Classification

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