Python Cnn-keras Resources

Explainable CNNs 📦 Flexible visualization package for generating layer-wise explanations for CNNs. It is a common notion that a Deep Learning model i

RNN 01- RNN_Classification Simple RNN training for classification task of 3 signal: Sine, Square, Triangle. 02- RNN_Regression Simple RNN training for

Training a NN to 99% accuracy on MNIST in 0.76 seconds A quick study on how fast you can reach 99% accuracy on MNIST with a single laptop. Our answer

Machine Learning Notebooks, 3rd edition This project aims at teaching you the fundamentals of Machine Learning in python. It contains the example code

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:

Fastformer Notes from the authors Pytorch/Keras implementation of Fastformer. The keras version only includes the core fastformer attention part. The

Image Classification in Python Implementing image classification in Flask using Keras. The VGG16 is a convolution neural network model architecture th

Structured Sparse R-CNN for Direct Scene Graph Generation Our paper Structured Sparse R-CNN for Direct Scene Graph Generation has been accepted by CVP

Transformers Arabic licence plate recognition 🚗 Solution to the kaggle competition Machathon 3.0. Ranked in the top 6️⃣ at the final evaluation phase

Intrusion-Detection-System-Using-CNN-and-Transfer-Learning This is the code for the paper entitled "A Transfer Learning and Optimized CNN Based Intrus

LG-AI-Challenge-for-Plant-Classification Dacon에서 진행된 농업 환경 변화에 따른 작물 병해 진단 AI 경진대회 에 대한 코드입니다. (colab directory에 코드가 잘 정리 되어있습니다.) Requirements python

ConvNeXt-TF This repository provides TensorFlow / Keras implementations of different ConvNeXt [1] variants. It also provides the TensorFlow / Keras mo

Potato Disease Classification Setup for Python: Install Python (Setup instructions) Install Python packages pip3 install -r training/requirements.txt

Basic Machine Learning This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resource

Soomvaar 📌 Introduction Soomvaar is the collection of various codes implement in machine learning and machine learning algorithms with python on coll

Bitcoin Realized Volatility Forecasting with GARCH and Multivariate LSTM Author: Chi Bui This Repository Repository Directory ├── README.md

Group R-CNN for Point-based Weakly Semi-supervised Object Detection (CVPR2022) By Shilong Zhang*, Zhuoran Yu*, Liyang Liu*, Xinjiang Wang, Aojun Zhou,

Classification models 1D Zoo - Keras and TF.Keras This repository contains 1D variants of popular CNN models for classification like ResNets, DenseNet

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction Requirements The code has been tested running under Python 3.7.4, with the foll

custom-cnn-fashion-mnist Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow. The following

Face Mask Detection The Model is designed to check if any human is wearing a mask or not. Dataset Description The Dataset contains a total of 11,792 i

Optical Character Recognition OCR (Optical Character Recognition) is a technology that enables the conversion of document types such as scanned paper

intro-to-cnn-p1 Repo for hosting workshop materials delivered on 28/02/2022 Questions you will answer in this workshop Learning Objectives What are co

Custom Keras ML block example for Edge Impulse This repository is an example on

Federated_Learning 💻 This projest include common test models for federated lear

Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab

Brain-Tumor-Detection Building a detection model using a convolutional neural network in Tensorflow & Keras. Used brain MRI images. InceptionResNetV2

OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.

Handwritten Character Recognition using CNN Problem Definition The main objective of this project is to solve the problem of handwritten character rec

C-CNN: Contourlet Convolutional Neural Networks This repo implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networ

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 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 is the process of increasing the number of training dataset. Keras library offers a simple

Tensorflow2 Keras-based Semantic Segmentation Models Implementation

Siren: Implicit Neural Representations with Periodic Activation Functions The unofficial Tensorflow 2 implementation of the paper Implicit Neural Repr

Detect and Classify Brain Tumor using CNN. A system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN).

Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!

keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o

Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in

CNN Detection (CS550 Machine Learning Project) Team Members (Tensor) : Yadava Kishore Chodipilli (11940310) Thashmitha BS (11941250) This is a work do

Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn

Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers This repository contains code to run experiments in the paper "Signal Stre

CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt

WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution This code belongs to the paper [1] available at https://arx

This repository contains the code for TABS, a 3D CNN-Transformer hybrid automated brain tissue segmentation algorithm using T1w structural MRI scans. TABS relies on a Res-Unet backbone, with a Vision Transformer embedded between the encoder and decoder layers.

SegTransVAE: Hybrid CNN - Transformer with Regularization for medical image segmentation This repo is the official implementation for SegTransVAE. Seg

Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).

ECAENet: EfficientNet with Efficient Channel Attention for Plant Species Recognition (SCI:Q3) (Journal of Intelligent & Fuzzy Systems)

Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of

Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the

cell_counting_v2 The repository includes the code for training cell counting applications. (Keras + Tensorflow) Dataset can be downloaded here : http:

ild-cnn This is supplementary material for the manuscript: "Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neur

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

This is an implementation of Volodymyr Mnih's dissertation methods on his Massachusetts road & building dataset and my original methods that are publi

FCN_MSCOCO_Food_Segmentation Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation Input data: [http://mscoco.org/dataset/#ove

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 This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed

Example-CNN-Project This is a simple project showing how to implement deep neural networks using CNN algorithm. The dataset is taken from this link: h

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

Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas

News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural

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 Histological Image Segmentation This

Keras-Image-Embeddings-using-Contrastive-Loss Image to Embedding projection in vector space. Implementation in keras and tensorflow for custom data. B

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

Software Used python - programming language used, tested on v3.8 miniconda - for managing virtual environment Libraries Used opencv - pip install open

keras_udrl Keras implementation of Upside Down Reinforcement Learning This is me

Pytorch Implementation of Augmenting Convolutional networks with attention-based aggregation This is the unofficial PyTorch Implementation of "Augment

Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification. - Classes is: Extremely Positive, Positive, Extremely Negativ

EfficientWord-Net Hotword detection based on one-shot learning Home assistants require special phrases called hotwords to get activated (eg:"ok google

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 mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har

Vietnamese sign lagnuage recognition using MHI and CNN This is a model to classify Vietnamese sign language using Motion history image (MHI) algorithm

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

Quantifying Hippocampus Volume for Alzheimer's Progression Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder that result

Traffic Signs Recognition ⚠️ 🚦 Fundamentals of Intelligent Systems Introduction 📄 Development of a neural network capable of recognizing nine differ

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 which will then be used to generate residuals

deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis

Tensorflow Implementation of "A ConvNet for the 2020s" This is the unofficial Tensorflow Implementation of ConvNeXt from "A ConvNet for the 2020s" pap

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

Trained image classification models for Keras THIS REPOSITORY IS DEPRECATED. USE THE MODULE keras.applications INSTEAD. Pull requests will not be revi

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

TensorFlow Tutorial - used by Nvidia Learn TensorFlow from scratch by examples and visualizations with interactive jupyter notebooks. Learn to compete

The Autonomous Driving Cookbook (Preview) NOTE: This project is developed and being maintained by Project Road Runner at Microsoft Garage. This is cur

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.

About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering

Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks arXiv preprint: https://arxiv.org/abs/2201.02143. Architec

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

Deep Learning with TensorFlow 2 and Keras – Notebooks This project accompanies my Deep Learning with TensorFlow 2 and Keras trainings. It contains the

keras-yolo3 Introduction A Keras implementation of YOLOv3 (Tensorflow backend) inspired by allanzelener/YAD2K. Quick Start Download YOLOv3 weights fro

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).

Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua

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 Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav

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 Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p

The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided

Generative Adversarial Notebooks Collection of my Generative Adversarial Network implementations Most codes are for python3, most notebooks works on C

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