convolutional-autoencoder

gabrieleilertsen/hdrcnn

HDR image reconstruction from a single exposure using deep CNNs

raadon96/MVTec-Anomaly-Detection

This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

koba-jon/pytorch_cpp

Deep Learning sample programs using PyTorch in C++

rezacsedu/Deep-Learning-for-Clustering-in-Bioinformatics

Deep Learning-based Clustering Approaches for Bioinformatics

hiram64/ocsvm-anomaly-detection

anomaly detection by one-class SVM

KAIST-VCLAB/deepcassi

[SIGGRAPH Asia 2017] High-Quality Hyperspectral Reconstruction Using a Spectral Prior

Nemzy/video_generator

This is implementation of convolutional variational autoencoder in TensorFlow library and it will be used for video generation.

andreaazzini/segnet.tf

SegNet-like Autoencoders in TensorFlow

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

ShrishtiHore/Anomaly-Detection-in-CCTV-Surveillance-Videos

This projects detect Anomalous Behavior through live CCTV camera feed to alert the police or local authority for faster response time. We are using Spatio Temporal AutoEncoder and more importantly three models from Keras ie; Convolutional 3D, Convolutional 2D LSTM and Convolutional 3D Transpose. 👮‍♂️👮‍♀️📹🔍🔫⚖

OliverEdholm/Convolutional-Autoencoder

A convolutional autoencoder made in TFLearn.

irdanish11/AnomalyEventDetection

Unsupervised deep learning system for local anomaly event detection in crowded scenes

ngailapdi/autoencoder

Implementation of a convolutional auto-encoder in PyTorch

alegonz/kdsb17

Gaussian Mixture Convolutional AutoEncoder applied to CT lung scans from the Kaggle Data Science Bowl 2017

ekremcet/AEFPNC

Image Denoising Using Deep Convolutional Autoencoder with Feature Pyramids

melissa135/Convolutional_AutoEncoder

A convolutional auto-encoder for compressing time sequence data of stocks.

MrDavidYu/TF_Convolutional_Autoencoder

Convolutional autoencoder for encoding/decoding RGB images in TensorFlow with high compression ratio

madhawav/PlayWithAutoEncoders

Image Compression on COCO Dataset using Convolution AutoEncoders

MLEnthusiast/conv-autoencoder

Unsupervised Image Retrieval with Convolutional Autoencoder in Tensorflow

xxl4tomxu98/autoencoder-feature-extraction

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

jczic/MicroNN

Micro neural network with multi-dimensional layers, multi-shaped data, fully or locally meshing, conv2D, unconv2D, Qlearning, ... for test!

sevagh/MiXiN

Music Xtraction with Nonstationary Gabor Transforms and Convolutional Denoising Autoencoders

tuvovan/ANL-HDRI

High Dynamic Range Image Synthesis via Attention Non-Local Network

aedera/deepredmt

Deepred-Mt is a novel method based on deep neural networks to predict C-to-U editing sites in angiosperm mitochondrial RNA.

gsiddhad/CAE-CAN

Implementation of Cancelable Biometric Template Generation using Convolutional Autoencoder

khanmhmdi/Cifar-Image-Reconstruction-using-Autoencoder-Models

Cifar-10 Image Reconstruction using Auto-encoder Models

jkaardal/matlab-convolutional-autoencoder

Cost function and cost gradient function for a convolutional autoencoder.

maxgraf96/DLAM_Assignment

End-To-End Raw Audio Resynthesis System for Piano -> E-Piano

ALPHAYA-Japan/autoencoders

Collection of autoencoder models in Tensorflow

jmmanley/conv-autoencoder

a convolutional autoencoder in python and keras.

AminBoumerdassi/EMRI_signal_detection

Detecting GW signals from extreme mass ratio inspirals using convolutional autoencoders

giannhskp/Software-Development-for-Algorithmic-Problems_Project-3

Time Series Forecasting using RNN, Anomaly Detection using LSTM Auto-Encoder and Compression using Convolutional Auto-Encoder

mainak-ghosh/AutoEncoder

Comparison of dimensionality reduction ability of different autoencoders on different datasets.

anikch/Image-denoising-using-convolutional-autoencoder

The objective is to add some noise to the images and then use an Convolutional Autoencoder to denoise them.

zjmagou/MLYPGrain2024

a combined Convolutional autoencoder - Random Forest regression model of grain production in the mid-lower Yangtze plains