1,268 skills found · Page 1 of 43
borisbanushev / StockpredictionaiIn this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
rbgirshick / RcnnR-CNN: Regions with Convolutional Neural Network Features
ellisdg / 3DUnetCNNPytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
shanglianlm0525 / PyTorch NetworksPytorch implementation of cnn network
yu4u / Age Gender EstimationKeras implementation of a CNN network for age and gender estimation
vlawhern / Arl EegmodelsThis is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
dalinvip / Cnn Lstm Bilstm Deepcnn Clstm In PytorchIn PyTorch Learing Neural Networks Likes CNN、BiLSTM
MrYxJ / Calculate Flops.pytorchThe calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)
tz28 / Chinese Number Gestures Recognition基于卷积神经网络的数字手势识别安卓APP，识别数字手势0-10（The number gestures recognition Android APP based on convolutional neural network(CNN), which can recognize the gestures corresponding number 0 to 10）
microsoft / O CNNO-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
weiaicunzai / Bag Of Tricks For Image Classification With Convolutional Neural Networksexperiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc
jiny2001 / Dcscn Super ResolutionA tensorflow implementation of "Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network", a deep learning based Single-Image Super-Resolution (SISR) model.
paulgavrikov / VisualkerasVisualkeras is a Python package to help visualize Keras (either standalone or included in TensorFlow) neural network architectures. It allows easy styling to fit most needs. This module supports layered style architecture generation which is great for CNNs (Convolutional Neural Networks), and a graph style architecture, which works great for most models including plain feed-forward networks.
UjjwalSaxena / Automold Road Augmentation LibraryThis library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.
philipxjm / Deep Convolution Stock Technical AnalysisUses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.
yu4u / Convnet DrawerPython script for illustrating Convolutional Neural Networks (CNN) using Keras-like model definitions
CSAILVision / NetDissectNetwork Dissection http://netdissect.csail.mit.edu for quantifying interpretability of deep CNNs.
jiegzhan / Multi Class Text Classification CnnClassify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.
qiexing / Face Landmark Localizationcnn network predict face landmarks (68 points) and head pose (3d pose, yaw,roll,pitch).
btgraham / SparseConvNet ArchivedSpatially-sparse convolutional networks. Allows processing of sparse 2, 3 and 4 dimensional data.Build CNNs on the square/cubic/hypercubic or triangular/tetrahedral/hyper-tetrahedral lattices.
