Double UNET Implementation in Tensor Flow using Keras, Semantic Segmentation, Deep Learning

In this video, we are going to implement a semantic segmentation architecture called DoubleUNET in TensorFlow 2. 3. 1 using Keras. DoubleUNET is an architecture specially designed for biomedical image segmentation. It consists of two UNET connected to each other in a sequence. The network consists of the Squeeze and Excitation Network and the Atrous Spatial Pyramid Pooling (ASPP) along with the other necessary components. The DoubleUNET takes an image as input and predicted two masks, from each UNET. DoubleUNET Paper: Code: Other semantic segmentation architecture implementation: UNET: RESUNET: VGG16 UNET: VGG19 UNET: RESNET50 UNET: Join this channel to get access to perks: