This high-performance setup with multiple GPUs is ideal for training complex models or working with large datasets, significantly reducing training time compared to local machine setups. This model has been trained using 4 CPUs because we have a configuration with 4 workers in common. If we use...
This dual approach allows LaneNet to handle multiple lanes simultaneously and distinguish between them. 3. Embedding Learning: A key feature of LaneNet is its use of embedding vectors. For each pixel classified as a lane, the network assigns an embedding vector that helps cluster pixels belonging ...