HomeIoT ModelsDeepLabV3-ResNet50

    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.

    Qualcomm® QCS8550
    QCS8550 (Proxy)
    TorchScriptQualcomm® AI Engine Direct
    821ms
    Inference Time
    3-12MB
    Memory Usage
    83GPU
    Layers

    Technical Details

    Model checkpoint:COCO_WITH_VOC_LABELS_V1
    Input resolution:513x513
    Number of parameters:39.6M
    Model size:151 MB

    Applicable Scenarios

    • Anomaly Detection
    • Inventory Management

    Licenses

    Source Model:BSD-3-CLAUSE
    Deployable Model:AI Model Hub License

    Supported IoT Devices

    • QCS8550 (Proxy)

    Supported IoT Chipsets

    • Qualcomm® QCS8550