DeepLabV3+ extends atrous convolution–based semantic segmentation with an encoder–decoder structure that refines object boundaries while preserving rich contextual information.
This model uses DeepLabV3+ with a ResNet-50 backbone, combining multi-scale context aggregation from atrous spatial pyramid pooling (ASPP) with a lightweight decoder for sharper segmentation outputs. It is well suited for semantic segmentation tasks in applications such as autonomous driving, robotics, and scene understanding, where accuracy and robustness are critical.
