autoencoder-architecture

There are 12 repositories under autoencoder-architecture topic.

  • 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. 👮‍♂️👮‍♀️📹🔍🔫⚖

    Language:Jupyter Notebook29218

  • DanuserLab/openLCH

    Live Cell Histology: Extracting latent features from label-free live cell images using Adversarial Autoencoders

    Language:Lua5201

  • ayulockin/deepgenerativemodeling

    Towards Generative Modeling from (variational) Autoencoder to DCGAN

    Language:Jupyter Notebook3201

  • AdityaTheDev/ReconstructionOfImage-Using-DeepAutoEnccoders

    Autoencoder is a type of neural network where the output layer has the same dimensionality as the input layer. In simpler words, the number of output units in the output layer is equal to the number of input units in the input layer. An autoencoder replicates the data from the input to the output in an unsupervised manner and is therefore sometimes referred to as a replicator neural network. The autoencoders reconstruct each dimension of the input by passing it through the network. It may seem trivial to use a neural network for the purpose of replicating the input, but during the replication process, the size of the input is reduced into its smaller representation. The middle layers of the neural network have a fewer number of units as compared to that of input or output layers. Therefore, the middle layers hold the reduced representation of the input. The output is reconstructed from this reduced representation of the input.

    Language:Jupyter Notebook1100

  • rakibhhridoy/ImageDenoisingUsing-AutoEncoders

    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.

    Language:Jupyter Notebook1001

  • andrewjUTSW/openLCH

    Live Cell Histology: Extracting latent features from label-free live cell images using Adversarial Autoencoders

    Language:Lua0102

  • dame-cell/Masked-AutoEncoders

    Pytorch implementation of Masked Autoencoder I

    Language:Python0200

  • jaynilpatel/autoencoder

    vanilla and convolutional autoencoder for generating mnist images

    Language:Jupyter Notebook0100

  • PrasunDatta/IEEE-Signal-Processing-Cup-2020_Unsupervied-Abnormality-Detection

    In this research work, unsupervised abnormality has been detected by using intelligent and heterogeneous autonomous systems.

    Language:Python0210

  • HayatiYrtgl/autoencoder_colorization

    Colorizes grayscale images using a loaded model and displays original and predicted colorized versions.

    Language:Python10

  • potatobox1/Person-Segmentation-with-Autoencoders

    Person Segmentation using custom Autoencoder architecture and evaluation using IoU and Dice metrics, will also include Unet architecture in the future.

    Language:Jupyter Notebook

  • toniesteves/keras-autoencoder-rgb-images

    Uma abordagem prática para construção de autoencoders convolucionais.

    Language:Python10