82 Open source projects that are alternatives of or similar to Cnn Lstm Bilstm Deepcnn Clstm In Pytorch

Repo of paper title 'Avoid touching your face: A hand-to-face 3d motion dataset (covid-away) and trained models for smartwatches'

A toolkit for neural language modeling using Tensorflow including basic models like RNNs and LSTMs as well as more advanced models.

.NET library to easily create Voice Command Control feature.

Relation Classification - SEMEVAL 2010 task 8 dataset

Load forcasting on Delhi area electric power load using ARIMA, RNN, LSTM and GRU models

language models toolkits with hierarchical softmax setting

pyTorch-text-classification

Keras implementation of a ResNet-CAM model

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

LSTM, GRU cell implementation from scratch in tensorflow

Official repo of the article: Yousef, W. A., Ibrahime, O. M., Madbouly, T. M., & Mahmoud, M. A. (2019), "Learning meters of arabic and english poems with recurrent neural networks: a step forward for language understanding and synthesis", arXiv preprint arXiv:1905.05700

Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification

Highway Networks implement in pytorch

My implementation of "Hierarchical Attention Networks for Document Classification" in Keras

🔬 Nano size Theano LSTM module

Pre-trained VGG-Net Model for image classification using tensorflow

Compare six baseline deep learning models on TrecQA

Convolutional GRU

百度云魅族深度学习应用大赛

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Deep Learning

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

[RSE21] Pytorch code for hierarchical time series classification with multi-stage convolutional RNN

Porting of Skip-Thoughts pretrained models from Theano to PyTorch & Torch7

Recurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano

Skripsi

Word Embedding + LSTM + FC

The project uses state of the art deep learning on collected data for automatic analysis of emotions.

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

Deep Learning models for network traffic classification

bitcoin prediction algorithms

Target detection and multi target tracking platform based on Yolo DeepSort and Flask.

Recurrent Additive Networks for Tensorflow

Predict Cryptocurrency Price with Deep Learning

Detecting and Predicting Forest Cover Change in Pakistani Areas Using Remote Sensing Imagery

A Keras library for multi-step time-series forecasting.

A menu based multiple chronic disease detection system which will detect if a person is suffering from a severe disease by taking an essential input image.

Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow

[PAMI 2021] Gating Revisited: Deep Multi-layer RNNs That Can Be Trained

Keras and PyTorch implementations of the MaLSTM model for computing Semantic Similarity.

RNN(LSTM, GRU) in Theano with mini-batch training; character-level language models in Theano

Optical Character Recognition in Swift for iOS&macOS. 银行卡、身份证、门牌号光学识别

Weapon Detection & Classification through CCTV surveillance using Deep Learning-CNNs.

This is my graduation project in BIT. Title: Noise Reduction Using GRU.

Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).

Part-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN

Haste: a fast, simple, and open RNN library

An RNN (GRU) TensorFlow Android App for word prediction.

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Keras tutorial for beginners (using TF backend)

This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

Implementation of Hierarchical Attention Networks in PyTorch

VGG-Face CNN descriptor in PyTorch.

CNN, RNN, and Bayesian NN classification for ECG time-series (using TensorFlow in Swift and Python)

Image Captcha Solving Using TensorFlow and CNN Model. Accuracy 90%+

Neural Machine Translation with Keras

ImageNet pre-trained models with batch normalization for the Caffe framework

Using Convolutional Neural Networks in speech emotion recognition on the RAVDESS Audio Dataset.

Genre Classification using Convolutional Neural Networks