Pinned Repositories
Andrew-Ng-Deep-Learning-notes
吴恩达《深度学习》系列课程笔记及代码
AndrewNg-DeepLearning
微专业: 吴恩达 深度学习工程师 作业
AndrewNgMachineLearning
matlab版的代码实现已全部完成吴恩达机器学习
Automatic-Emotion-Recognition-on-DEAP-Dataset
The project uses EEG signals from the DEAP Dataset to classify emotions into 4 classes using Ensembled 1-D CNNs, LSTMs and 2D , 3D CNNs and Cascaded CNNs with LSTMs.
Awesome-Chinese-NLP
A curated list of resources for Chinese NLP 中文自然语言处理相关资料
Brain_typing
Codes, data for brain typing paper.
char-rnn
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
deap-cnn-lstm
Emotion recognition based on DEAP dataset using One-Dimensional CNN, dan RNN (GRU, and LSTM).
EEG-Based-Emotion-Recognition-on-DEAP
Emotion-Recognition-from-brain-EEG-signals-
Emotion recognition can be achieved by obtaining signals from the brain by EEG . This test records the activity of the brain in form of waves. We have used DEAP dataset on which we are classifying the emotion as valance, likeness/dislike, arousal, dominance. We have used LSTM and CNN classifier which gives 88.60 % accuracy to predict the model successfully.
dlzln's Repositories
dlzln/Automatic-Emotion-Recognition-on-DEAP-Dataset
The project uses EEG signals from the DEAP Dataset to classify emotions into 4 classes using Ensembled 1-D CNNs, LSTMs and 2D , 3D CNNs and Cascaded CNNs with LSTMs.
dlzln/Brain_typing
Codes, data for brain typing paper.
dlzln/deap-cnn-lstm
Emotion recognition based on DEAP dataset using One-Dimensional CNN, dan RNN (GRU, and LSTM).
dlzln/EEG-Based-Emotion-Recognition-on-DEAP
dlzln/Emotion-Recognition-from-brain-EEG-signals-
Emotion recognition can be achieved by obtaining signals from the brain by EEG . This test records the activity of the brain in form of waves. We have used DEAP dataset on which we are classifying the emotion as valance, likeness/dislike, arousal, dominance. We have used LSTM and CNN classifier which gives 88.60 % accuracy to predict the model successfully.
dlzln/Andrew-Ng-Deep-Learning-notes
吴恩达《深度学习》系列课程笔记及代码
dlzln/AndrewNg-DeepLearning
微专业: 吴恩达 深度学习工程师 作业
dlzln/AndrewNgMachineLearning
matlab版的代码实现已全部完成吴恩达机器学习
dlzln/Awesome-Chinese-NLP
A curated list of resources for Chinese NLP 中文自然语言处理相关资料
dlzln/char-rnn
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
dlzln/Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
dlzln/Deep-Learning-with-PyTorch-Tutorials
深度学习与PyTorch入门实战视频教程
dlzln/deeplearning-assignment
吴恩达-深度学习-课后作业-答案与总结
dlzln/dlzln
Config files for my GitHub profile.
dlzln/event-related-desynchronization
Motor imagery EEG classifier for my master's thesis.
dlzln/examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
dlzln/learning_to_execute
Learning to Execute
dlzln/Libsvm-FarutoUltimate-Version
Libsvm-FarutoUltimate Version
dlzln/lstm
Minimal, clean example of lstm neural network training in python, for learning purposes.
dlzln/Multi-target_Location_and_Tracking_with_WSN
Multi-target localization and tracking with Wireless Sensor Networks for digital-storytelling
dlzln/NegotiationSpin
The Spin mode source for the proposed negotiation protocol.
dlzln/neuraltalk
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
dlzln/omnetpp_primer
OMNeT++的仿真手册
dlzln/pytorch-handbook
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
dlzln/sentence-completion
A pytorch implementation of the word-level recurrent neural network for sentence completion
dlzln/WirelessSensorNetwork_Protocols
Implementation of major WSN protocols: SPIN, Gossip, Flooding. Their performance analyses and comparison.
dlzln/WSN-localization
WSN, Localization, APIT, DV-HOP, MDS-MAP
dlzln/WSN_LEECH_Potocol
Implementation of LEACH (Low-energy adaptive clustering hierarchy) Protocols