Autoencoder architecture is used to build a model that can learn to produce a segmentation mask from the input image. Intuitively, the output of the autoencoder is expected to be the predicted ...

Project Overview BrainSeg leverages autoencoder ... segmentation masks highlighting tumor regions. Architecture Details Encoder: Multiple convolutional layers with residual connections for feature ...

More specifically, we dive into the scope of remote-sensing, or aerial, images and how convolutional neural networks help analyze such images using techniques like semantic segmentation. We compare a ...