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
Supported Form Factors
- Phone
- Tablet
- IoT
Licenses
Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License
Supported Devices
- QCS8550 (Proxy)
- SA8255 (Proxy)
- SA8295P ADP
- SA8650 (Proxy)
- SA8775P ADP
- Samsung Galaxy S21
- Samsung Galaxy S21 Ultra
- Samsung Galaxy S21+
- Samsung Galaxy S22 5G
- Samsung Galaxy S22 Ultra 5G
- Samsung Galaxy S22+ 5G
- Samsung Galaxy S23
- Samsung Galaxy S23 Ultra
- Samsung Galaxy S23+
- Samsung Galaxy S24
- Samsung Galaxy S24 Ultra
- Samsung Galaxy S24+
- Samsung Galaxy Tab S8
- Snapdragon 8 Elite QRD
- Snapdragon X Elite CRD
- Snapdragon X Plus 8-Core CRD
- Xiaomi 12
- Xiaomi 12 Pro
Supported Chipsets
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® SA8255P (Proxy)
- Qualcomm® SA8295P
- Qualcomm® SA8650P (Proxy)
- Qualcomm® SA8775P
- Snapdragon® 8 Elite Mobile
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
- Snapdragon® X Elite
- Snapdragon® X Plus 8-Core
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