331 Repositories
Python keras-crnn Libraries
Repository for RNNs using TensorFlow and Keras - LSTM and GRU Implementation from Scratch - Simple Classification and Regression Problem using RNNs
RNN 01- RNN_Classification Simple RNN training for classification task of 3 signal: Sine, Square, Triangle. 02- RNN_Regression Simple RNN training for
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Machine Learning Notebooks, 3rd edition This project aims at teaching you the fundamentals of Machine Learning in python. It contains the example code
tf2-keras implement yolov5
YOLOv5 in tesnorflow2.x-keras yolov5数据增强jupyter示例 Bilibili视频讲解地址: 《yolov5 解读,训练,复现》 Bilibili视频讲解PPT文件: yolov5_bilibili_talk_ppt.pdf Bilibili视频讲解PPT文件:
A pytorch &keras implementation and demo of Fastformer.
Fastformer Notes from the authors Pytorch/Keras implementation of Fastformer. The keras version only includes the core fastformer attention part. The
A python-image-classification web application project, written in Python and served through the Flask Microframework. This Project implements the VGG16 covolutional neural network, through Keras and Tensorflow wrappers, to make predictions on uploaded images.
Image Classification in Python Implementing image classification in Flask using Keras. The VGG16 is a convolution neural network model architecture th
Includes PyTorch - Keras model porting code for ConvNeXt family of models with fine-tuning and inference notebooks.
ConvNeXt-TF This repository provides TensorFlow / Keras implementations of different ConvNeXt [1] variants. It also provides the TensorFlow / Keras mo
Potato Disease Classification - Training, Rest APIs, and Frontend to test.
Potato Disease Classification Setup for Python: Install Python (Setup instructions) Install Python packages pip3 install -r training/requirements.txt
This is a repo of basic Machine Learning!
Basic Machine Learning This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resource
Soomvaar is the repo which 🏩 contains different collection of 👨💻🚀code in Python and 💫✨Machine 👬🏼 learning algorithms📗📕 that is made during 📃 my practice and learning of ML and Python✨💥
Soomvaar 📌 Introduction Soomvaar is the collection of various codes implement in machine learning and machine learning algorithms with python on coll
GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management
Bitcoin Realized Volatility Forecasting with GARCH and Multivariate LSTM Author: Chi Bui This Repository Repository Directory ├── README.md
Classification models 1D Zoo - Keras and TF.Keras
Classification models 1D Zoo - Keras and TF.Keras This repository contains 1D variants of popular CNN models for classification like ResNets, DenseNet
Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow.
custom-cnn-fashion-mnist Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow. The following
Comparison-of-OCR (KerasOCR, PyTesseract,EasyOCR)
Optical Character Recognition OCR (Optical Character Recognition) is a technology that enables the conversion of document types such as scanned paper
Example-custom-ml-block-keras - Custom Keras ML block example for Edge Impulse
Custom Keras ML block example for Edge Impulse This repository is an example on
OMLT: Optimization and Machine Learning Toolkit
OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.
Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset
SW-CV-ModelZoo Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset Framework: TF/Keras 2.7 Training SQLite D
Image Data Augmentation in Keras
Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset.
Data Augmentation Using Keras and Python
Data-Augmentation-Using-Keras-and-Python Data augmentation is the process of increasing the number of training dataset. Keras library offers a simple
A convolutional recurrent neural network for classifying A/B phases in EEG signals recorded for sleep analysis.
CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions
Siren: Implicit Neural Representations with Periodic Activation Functions The unofficial Tensorflow 2 implementation of the paper Implicit Neural Repr
Evaluation framework for testing segmentation networks in PyTorch
Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
Multi-label classification of retinal disorders
Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).
ECAENet (TensorFlow and Keras)
ECAENet: EfficientNet with Efficient Channel Attention for Plant Species Recognition (SCI:Q3) (Journal of Intelligent & Fuzzy Systems)
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images
Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the
The repository includes the code for training cell counting applications. (Keras + Tensorflow)
cell_counting_v2 The repository includes the code for training cell counting applications. (Keras + Tensorflow) Dataset can be downloaded here : http:
Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation
FCN_MSCOCO_Food_Segmentation Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation Input data: [http://mscoco.org/dataset/#ove
This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks
NNProject - DeepMask This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks. Th
Segmentation Training Pipeline
Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed
Creating Multi Task Models With Keras
Creating Multi Task Models With Keras About The Project! I used the keras and Tensorflow Library, To build a Deep Learning Neural Network to Creating
To prepare an image processing model to classify the type of disaster based on the image dataset
Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas
This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.
News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural
Keras Image Embeddings using Contrastive Loss
Image to Embedding projection in vector space. Implementation in keras and tensorflow of batch all triplet loss for one-shot/few-shot learning.
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This
Keras Image Embeddings using Contrastive Loss
Keras-Image-Embeddings-using-Contrastive-Loss Image to Embedding projection in vector space. Implementation in keras and tensorflow for custom data. B
This Deep Learning Model Predicts that from which disease you are suffering.
Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int
Keras udrl - Keras implementation of Upside Down Reinforcement Learning
keras_udrl Keras implementation of Upside Down Reinforcement Learning This is me
Face Mask Detector by live camera using tensorflow-keras, openCV and Python
Face Mask Detector 😷 by Live Camera Detecting masked or unmasked faces by live camera with percentange of mask occupation About Project: This an Arti
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har
The final project of "Applying AI to 2D Medical Imaging Data" of "AI for Healthcare" nanodegree - Udacity.
Pneumonia Detection from X-Rays Project Overview In this project, you will apply the skills that you have acquired in this 2D medical imaging course t
The final project of "Applying AI to 3D Medical Imaging Data" from "AI for Healthcare" nanodegree - Udacity.
Quantifying Hippocampus Volume for Alzheimer's Progression Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder that result
IA for recognising Traffic Signs using Keras [Tensorflow]
Traffic Signs Recognition ⚠️ 🚦 Fundamentals of Intelligent Systems Introduction 📄 Development of a neural network capable of recognizing nine differ
Convnext-tf - Unofficial tensorflow keras implementation of ConvNeXt
ConvNeXt Tensorflow This is unofficial tensorflow keras implementation of ConvNe
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals
Unofficial Tensorflow Implementation of ConvNeXt from A ConvNet for the 2020s
Tensorflow Implementation of "A ConvNet for the 2020s" This is the unofficial Tensorflow Implementation of ConvNeXt from "A ConvNet for the 2020s" pap
Keras implementations of Generative Adversarial Networks.
This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as
Keras code and weights files for popular deep learning models.
Trained image classification models for Keras THIS REPOSITORY IS DEPRECATED. USE THE MODULE keras.applications INSTEAD. Pull requests will not be revi
Jupyter notebooks for using & learning Keras
deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例
Scenarios, tutorials and demos for Autonomous Driving
The Autonomous Driving Cookbook (Preview) NOTE: This project is developed and being maintained by Project Road Runner at Microsoft Garage. This is cur
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Chess reinforcement learning by AlphaGo Zero methods.
About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering
Text classification on IMDB dataset using Keras and Bi-LSTM network
Text classification on IMDB dataset using Keras and Bi-LSTM Text classification on IMDB dataset using Keras and Bi-LSTM network. Usage python3 main.py
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
Deep Learning with TensorFlow 2 and Keras – Notebooks This project accompanies my Deep Learning with TensorFlow 2 and Keras trainings. It contains the
A Keras implementation of YOLOv3 (Tensorflow backend)
keras-yolo3 Introduction A Keras implementation of YOLOv3 (Tensorflow backend) inspired by allanzelener/YAD2K. Quick Start Download YOLOv3 weights fro
This repo contains the implementation of YOLOv2 in Keras with Tensorflow backend.
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
A Neural Network based chess engine and GUI made with Python and Tensorflow/Keras.
Haxaw-Chess Haxaw: Haxaw is the Neural Network based chess engine made with Python and Tensorflow/Keras. Also uses the python-chess library. (WIP: Imp
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav
An example of time series augmentation methods with Keras
Time Series Augmentation This is a collection of time series data augmentation methods and an example use using Keras. News 2020/04/16: Repository Cre
WTTE-RNN a framework for churn and time to event prediction
WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p
wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
Generative Adversarial Notebooks Collection of my Generative Adversarial Network implementations Most codes are for python3, most notebooks works on C
Setup and customize deep learning environment in seconds.
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le
Keras documentation, hosted live at keras.io
Keras.io documentation generator This repository hosts the code used to generate the keras.io website. Generating a local copy of the website pip inst
make ASCII Art by Deep Learning
DeepAA This is convolutional neural networks generating ASCII art. This repository is under construction. This work is accepted by NIPS 2017 Workshop,
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
Single Image Super-Resolution with EDSR, WDSR and SRGAN A Tensorflow 2.x based implementation of Enhanced Deep Residual Networks for Single Image Supe
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
Face Mask Detection Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix
🏖 Keras Implementation of Painting outside the box
Keras implementation of Image OutPainting This is an implementation of Painting Outside the Box: Image Outpainting paper from Standford University. So
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Fine tuning keras-ocr python package with custom synthetic dataset from scratch
OCR-Pipeline-with-Keras The keras-ocr package generally consists of two parts: a Detector and a Recognizer: Detector is responsible for creating bound
An image classification app boilerplate to serve your deep learning models asap!
Image 🖼 Classification App Boilerplate Have you been puzzled by tons of videos, blogs and other resources on the internet and don't know where and ho
Deep-Learning-Image-Captioning - Implementing convolutional and recurrent neural networks in Keras to generate sentence descriptions of images
Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================
Seq2seq - Sequence to Sequence Learning with Keras
Seq2seq Sequence to Sequence Learning with Keras Hi! You have just found Seq2Seq. Seq2Seq is a sequence to sequence learning add-on for the python dee
Keras-retinanet - Keras implementation of RetinaNet object detection.
Keras RetinaNet Keras implementation of RetinaNet object detection as described in Focal Loss for Dense Object Detection by Tsung-Yi Lin, Priya Goyal,
PConv-Keras - Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai
Partial Convolutions for Image Inpainting using Keras Keras implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions", https
Speech-Emotion-Analyzer - The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Keras Realtime Multi-Person Pose Estimation - Keras version of Realtime Multi-Person Pose Estimation project
This repository has become incompatible with the latest and recommended version of Tensorflow 2.0 Instead of refactoring this code painfully, I create
Client - 🔥 A tool for visualizing and tracking your machine learning experiments
Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ
Predictive Maintenance LSTM
Predictive-Maintenance-LSTM - Predictive maintenance study for Complex case study, we've obtained failure causes by operational error and more deeply by design mistakes.
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto
View model summaries in PyTorch!
torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘
Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear
ncnn is a high-performance neural network inference framework optimized for the mobile platform
ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme
Indonesian Car License Plate Character Recognition using Tensorflow, Keras and OpenCV.
Monopol Indonesian Car License Plate (Indonesia Mobil Nomor Polisi) Character Recognition using Tensorflow, Keras and OpenCV. Background This applicat
A deep learning model for style-specific music generation.
DeepJ: A model for style-specific music generation https://arxiv.org/abs/1801.00887 Abstract Recent advances in deep neural networks have enabled algo
Automatic meme generation model using Tensorflow Keras.
Memefly You can find the project at MemeflyAI. Contributors Nick Buukhalter Harsh Desai Han Lee Project Overview Trello Board Product Canvas Automatic
Yolact-keras实例分割模型在keras当中的实现
Yolact-keras实例分割模型在keras当中的实现 目录 性能情况 Performance 所需环境 Environment 文件下载 Download 训练步骤 How2train 预测步骤 How2predict 评估步骤 How2eval 参考资料 Reference 性能情况 训练数
Attempt at implementation of a simple GAN using Keras
Simple GAN This is my attempt to make a wrapper class for a GAN in keras which can be used to abstract the whole architecture process. Simple GAN Over
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017
AdaptationSeg This is the Python reference implementation of AdaptionSeg proposed in "Curriculum Domain Adaptation for Semantic Segmentation of Urban
Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation.
PersonLab This is a Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation. The model predicts heatmaps and vari
Header-only library for using Keras models in C++.
frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would
SE-MSCNN: A Lightweight Multi-scaled Fusion Network for Sleep Apnea Detection Using Single-Lead ECG Signals
SE-MSCNN: A Lightweight Multi-scaled Fusion Network for Sleep Apnea Detection Using Single-Lead ECG Signals Abstract Sleep apnea (SA) is a common slee
TensorFlow implementation of "TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?"
TokenLearner: What Can 8 Learned Tokens Do for Images and Videos? Source: Improving Vision Transformer Efficiency and Accuracy by Learning to Tokenize
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.
Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend
Deep Reinforcement Learning for Keras.
Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml