Image-Segementation-CamVid-using-SegNet

Data

• The Cambridge-driving Labeled Video Database (CamVid) provides ground truth labels that associate each pixel with one of 32 semantic classes. This dataset is often used in (real-time) semantic segmentation research.

• CamVid Data

Model

• The model used in this project is Segnet model
• SegNet is a semantic segmentation model. This core trainable segmentation architecture consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer.

Results

• as we can see, we reached an acuracy of 90% in test set, improved using Batch Normalization