Detecting malicious URLs using an autoencoder neural network

Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

Using convolutional autoencoders to remove random noise from seismic data.

Training Deep AutoEncoders for Collaborative Filtering

A collection of scripts and code for processing CPI-3V data

Autoencoder for Feature Extraction

All course material and codes of Generative Adversarial Networks Specialization offered by DeepLearning.ai

Bias field correction for T-1 weighted MRI images for tumor detection

Comparison of multiple methods for calculating MNIST hand-written digits similarity.

Natural Disaster Analysis Website using Deep Learning & Poisson Distribution

This research project intent is to review and demonstrate a comparability among recent auto-encoder methods by utilizing single architecture and resolution. Each method will be ranked based on selective performance measure in modeling healthy brain and the sensitivity towards domain shift.

➕💓Let's build the Simplest Possible Autoencoder . ⁉️🏷We'll start Simple, with a Single fully-connected Neural Layer as Encoder and as Decoder. 👨🏻‍💻🌟An Autoencoder is a type of Artificial Neural Network used to Learn Efficient Data Codings in an unsupervised manner🌘🔑

Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.

This project detect anomalous event in CCTV footage. For the training purposes only normal events are used. When any violence or anomalous event happen the model can detect it.

Use auto encoder feature extraction to facilitate classification model prediction accuracy using gradient boosting models

Filtering out the noise presented in the image by auto-enconder algorithm in TensorFow and Keras. Rare images, unclean crime images,medical noise images can be denoised and find out the desired outcome by using auto-encoders.

This repository represents an Auto-Encoder which can Encode and Decode itself and give the output at the output layer

Python autoencoder to remove blur from images

autoencoders