An autoencoder is an unsupervised neural network that learns to encode and reconstruct input images, making it useful for identifying outliers or anomalies. image-anomaly-with-autoencoder.ipynb → ...

The training approach is always training the 2 sized bottleneck along with the input custom size. To ensure the non-familiarity with test data for both models, I chose to save the test data fin the ...

Abstract: In this paper, we propose a DISCO, which is a manner of designing autoencoder architecture to process dual input streams for skeletal image generation. The DISCO was designed to be dealing ...

The network reconstructs the input data in a much similar way by learning its representation. The basic architecture of am Autoencoder is shown below. (Image Source: Wikipedia) The architecture ...

The convolutional autoencoder abandons the stacked data, keeps its spatial information unchanged when the image data is input, and gently extracts the information in the convolutional layer. This ...