rogertrullo / Pytorch_convlstm
convolutional lstm implementation in pytorch
Stars: ✭ 126
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Pytorch convlstm
Pytorch Learners Tutorial
PyTorch tutorial for learners
Stars: ✭ 97 (-23.02%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn, lstm
Deepseqslam
The Official Deep Learning Framework for Route-based Place Recognition
Stars: ✭ 49 (-61.11%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn, lstm
Tf Adnet Tracking
Deep Object Tracking Implementation in Tensorflow for 'Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning(CVPR 2017)'
Stars: ✭ 162 (+28.57%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Pyconv
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)
Stars: ✭ 231 (+83.33%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Personality Detection
Implementation of a hierarchical CNN based model to detect Big Five personality traits
Stars: ✭ 338 (+168.25%)
Mutual labels: convolutional-neural-networks, cnn, lstm
Iresnet
Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)
Stars: ✭ 163 (+29.37%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Hyperdensenet
This repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios.
Stars: ✭ 124 (-1.59%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Livianet
This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"
Stars: ✭ 143 (+13.49%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Rmdl
RMDL: Random Multimodel Deep Learning for Classification
Stars: ✭ 375 (+197.62%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Deepface
Deep Learning Models for Face Detection/Recognition/Alignments, implemented in Tensorflow
Stars: ✭ 409 (+224.6%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Easy Deep Learning With Keras
Keras tutorial for beginners (using TF backend)
Stars: ✭ 367 (+191.27%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, lstm
Gtsrb
Convolutional Neural Network for German Traffic Sign Recognition Benchmark
Stars: ✭ 65 (-48.41%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Lenet 5
PyTorch implementation of LeNet-5 with live visualization
Stars: ✭ 122 (-3.17%)
Mutual labels: deep-neural-networks, convolutional-neural-networks, cnn
Sarcasmdetection
Sarcasm detection on tweets using neural network
Stars: ✭ 99 (-21.43%)
Mutual labels: cnn, lstm
Awslambdaface
Perform deep neural network based face detection and recognition in the cloud (via AWS lambda) with zero model configuration or tuning.
Stars: ✭ 98 (-22.22%)
Mutual labels: deep-neural-networks, convolutional-neural-networks
Keras Video Classifier
Keras implementation of video classifier
Stars: ✭ 100 (-20.63%)
Mutual labels: convolutional-neural-networks, lstm
Har Keras Cnn
Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras
Stars: ✭ 97 (-23.02%)
Mutual labels: deep-neural-networks, convolutional-neural-networks
Top Deep Learning
Top 200 deep learning Github repositories sorted by the number of stars.
Stars: ✭ 1,365 (+983.33%)
Mutual labels: deep-neural-networks, convolutional-neural-networks
pytorch_convlstm
This is my attempt to implement convolutional lstm in pytorch. This idea has been proposed in this paper: Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
It's still in progress..
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].