DeepLabV3-ResNet50
Deep Convolutional Neural Network model for semantic segmentation.
DeepLabV3 is designed for semantic segmentation at multiple scales, trained on the COCO dataset. It uses ResNet50 as a backbone.
Technical Details
Model checkpoint:COCO_WITH_VOC_LABELS_V1
Input resolution:513x513
Number of parameters:39.6M
Model size:151 MB
Number of output classes:21
Applicable Scenarios
- Anomaly Detection
- Inventory Management
Licenses
Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License
Supported Automotive Devices
- SA8255 (Proxy)
- SA8650 (Proxy)
- SA8775 (Proxy)
Supported Automotive Chipsets
- Qualcomm® SA8255P (Proxy)
- Qualcomm® SA8650P (Proxy)
- Qualcomm® SA8775P (Proxy)