auto-encoders | Topic | Ecosyste.ms: Repos

Topic: "auto-encoders"

ankonzoid/artificio

Deep Learning Computer Vision Algorithms for Real-World Use

Language: Python - Size: 2.88 MB - Last synced at: 5 months ago - Pushed at: over 2 years ago - Stars: 411 - Forks: 217

oke-aditya/image_similarity

PyTorch Blog Post On Image Similarity Search

Language: Python - Size: 7.16 MB - Last synced at: 17 days ago - Pushed at: almost 3 years ago - Stars: 257 - Forks: 61

dali92002/DocEnTR

DocEnTr: An end-to-end document image enhancement transformer - ICPR 2022

Language: Jupyter Notebook - Size: 11.6 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 145 - Forks: 33

jayshah19949596/DeepSign-A-Deep-Learning-Architecture-for-Sign-Language-Recognition

Language: Python - Size: 59.9 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 44 - Forks: 19

msultan/vde_metadynamics

Enhanced protein mutational sampling using time-lagged variational autoencoders

Language: Python - Size: 87.2 MB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 26 - Forks: 6

mdeff/dlaudio

Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (code)

Language: Jupyter Notebook - Size: 86.9 KB - Last synced at: 20 days ago - Pushed at: about 5 years ago - Stars: 15 - Forks: 6

luckycallor/CDAAE

This is the code of experiments in paper Cross-Domain Adversarial Auto-Encoder(https://arxiv.org/abs/1804.06078)

Language: Python - Size: 28.3 KB - Last synced at: over 1 year ago - Pushed at: about 7 years ago - Stars: 11 - Forks: 3

Ankit-Kumar-Saini/Coursera_TensorFlow_Advanced_Techniques_Specialization

Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.

Language: Jupyter Notebook - Size: 53.9 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 9 - Forks: 4

mdeff/dlaudio_report

Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (report)

Language: TeX - Size: 303 KB - Last synced at: about 1 month ago - Pushed at: about 5 years ago - Stars: 6 - Forks: 0

Gaurav-Pande/Recommendation_systems

Auto encoders based recommendation system

Language: Python - Size: 3.45 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 5 - Forks: 1

ResByte/pytorch-gan

Modified and example codes of GAN in pytorch

Language: Jupyter Notebook - Size: 242 KB - Last synced at: 21 days ago - Pushed at: over 5 years ago - Stars: 4 - Forks: 1

navigator8972/pcae

Point Cloud Gaussian Mixture Models and Shape Completion with Auto-encoder embeddings

Language: Jupyter Notebook - Size: 1.2 MB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 4 - Forks: 2

saadhaxxan/Application-of-Convolutional-AutoEncoders

Language: Jupyter Notebook - Size: 1020 KB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 3 - Forks: 0

Sujay8070/Image-Denoising

My research work with a proof of concept for Image Restoration of motion-blurred images in Real-time using data augmentation and specific architecture of Deep Autoencoder network (inspired from U-Net model) with CNN layers. (Studied extensive use of functional APIs for custom layers, loss, and metrics, effects of regularization & Hyperparams optimization), IDE/ Frameworks/ Libraries used: [Google Colab, TensorFlow, Keras, Scikit-learn, and OpenCV among others. others.

Language: Jupyter Notebook - Size: 4.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 0

sm823zw/Noise-Removal-from-Medical-Images

In this repository, denoising of medical images has been performed using convolutional auto-encoder models.

Language: Jupyter Notebook - Size: 17.2 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0

j-sripad/VAE

simple VAE pytorch implementation

Language: Python - Size: 1020 KB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

mdeff/dlaudio_results

Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (results)

Language: Jupyter Notebook - Size: 17.7 MB - Last synced at: about 1 month ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 1

vigneshramk/Meta-Learning-Generalizing-Speech-Denoising

Language: C - Size: 2.19 GB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 2 - Forks: 1

amshrbo/Machine-Learning-and-Deep-Learning-Models

In this repository, I'm going to include some well documented projects, that I've implemented during my learning and I will keep it updated

Language: Jupyter Notebook - Size: 657 KB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 1 - Forks: 0

aizen-rish/fraud-detection-using-deep-neural-networks

A module of Fraud detection in Credit card applications

Language: Python - Size: 6.95 MB - Last synced at: almost 2 years ago - Pushed at: almost 7 years ago - Stars: 1 - Forks: 0

TLESORT/torch-autoencoder

Language: Lua - Size: 13.7 KB - Last synced at: about 2 months ago - Pushed at: almost 8 years ago - Stars: 1 - Forks: 0

maettuu/24FS-Deep-Learning

Repository for the course Deep Learning Spring 2024

Language: Jupyter Notebook - Size: 1.51 MB - Last synced at: 2 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

sarojinisharon/Autoencoder-and-Variational-Autoencoder-Exploration-with-Fashion-MNIST

This project implements and compares Autoencoders (AEs) and Variational Autoencoders (VAEs) using the Fashion MNIST dataset. The project is ideal for those seeking to understand and apply deep learning techniques in unsupervised learning.

Language: Python - Size: 0 Bytes - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

adrianmarino/thesis-paper

Collaborative and hybrid recommendation systems

Language: Jupyter Notebook - Size: 353 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 1

jvmolu/Network-Anomaly-Detection

Explore Network Anomaly Detection Project 📊💻. It achieves an exceptional 99.7% accuracy through a blend of supervised and unsupervised learning, extensive feature selection, and model experimentation. Stunning data visualizations using synthetic network traffic data offer insightful representations of anomalies, enhancing network security.

Language: Jupyter Notebook - Size: 4.28 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0