DeepLabXception
Deep Convolutional Neural Network model for semantic segmentation.
DeepLabXception is a semantic segmentation model supporting multiple backbones like ResNet‑101 and Xception, with flexible dataset compatibility including COCO, VOC, and Cityscapes.
Technical Details
Model checkpoint:COCO_WITH_VOC_LABELS_V1
Input resolution:480x520
Number of output classes:21
Number of parameters:41.26M
Model size (float):158 MB
Applicable Scenarios
- Anomaly Detection
- Inventory Management
Licenses
Source Model:BSD-3-CLAUSE
Deployable Model:AI-HUB-MODELS-LICENSE
Supported Compute Devices
- Snapdragon X Elite CRD
- Snapdragon X Plus 8-Core CRD
Supported Compute Chipsets
- Snapdragon® X Elite
- Snapdragon® X Plus 8-Core
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