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Projects in Awesome Lists tagged with convolutional-autoencoder

A curated list of projects in awesome lists tagged with convolutional-autoencoder .

https://github.com/madhawav/playwithautoencoders

Image Compression on COCO Dataset using Convolution AutoEncoders

autoencoder computer-graphics computer-vision convolutional-autoencoder image-compression pytorch

Last synced: 18 Mar 2025

https://github.com/jczic/micronn

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

artificial-intelligence autoencoder-neural-network convolutional-autoencoder convolutional-neural-networks deep-learning jczic machine-learning mlp-classifier neural-network neural-networks neurons python q-learning qlearning reinforcement-learning

Last synced: 19 Mar 2025

https://github.com/sevagh/mixin

Music Xtraction with Nonstationary Gabor Transforms and Convolutional Denoising Autoencoders

convolutional-autoencoder convolutional-neural-networks cqt-spectrogram deep-learning gabor-analysis music-separation source-separation

Last synced: 12 Jun 2025

https://github.com/tuvovan/anl-hdri

High Dynamic Range Image Synthesis via Attention Non-Local Network

attention-network convolutional-autoencoder convolutional-neural-networks hdr-image hdr-imaging

Last synced: 08 Jul 2025

https://github.com/aaaastark/accelerometer-sensors-analysis

Time Series Analysis: Accelerometer Sensors of Object Inclination and Vibration. Time Series Analysis by using different (State of Art Models) Machine and Deep Learning. Recurent Neural Network with CuDNNLSTM Model, Convolutional Autoencoder, Residual Network (ResNet) and MobileNet Model.

accelerator accelerometer convolutional-autoencoder cudnnlstm inclination keras markov-transition-fields matplotlib moblienet pandas python recurrent-neural-network residual-network sensor sensors-data-collection skleran tensorflow time-series-analysis vibration-analysis vibration-sensor

Last synced: 07 Apr 2026

https://github.com/sureshbeekhani/autoencoders

This project is a practice implementation of an autoencoder, The primary use case for this autoencoder is for anomaly detection in sales data, but it can be adapted for other purposes. The autoencoder compresses the input data into a lower-dimensional representation and then reconstructs the original input from this representation.

autoencoder convolutional-autoencoder data-compression data-reconstruction deep-learning denoising-autoencoder generative-models image-processing latent-space machine-learning neural-networks vanilla-autoencoder variational-autoencode

Last synced: 04 Sep 2025