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    DeepLabV3-Plus-MobileNet-Quantized

    Quantized Deep Convolutional Neural Network model for semantic segmentation.

    DeepLabV3 Quantized is designed for semantic segmentation at multiple scales, trained on various datasets. It uses MobileNet as a backbone.

    3.53ms
    Inference Time
    0-17MB
    Memory Usage
    99NPU
    Layers
    See more metrics
    Model RepositoryHugging FaceResearch Paper

    Technical Details

    Model checkpoint:VOC2012
    Input resolution:513x513
    Number of parameters:5.80M
    Model size:6.04 MB

    Applicable Scenarios

    • Anomaly Detection
    • Inventory Management

    Licenses

    Source Model:MIT
    Deployable Model:AI Model Hub License

    Tags

    • quantized
      A “quantized” model can run in low or mixed precision, which can substantially reduce inference latency.

    Supported IoT Devices

    • QCS6490 (Proxy)
    • QCS8250 (Proxy)
    • QCS8550 (Proxy)
    • RB3 Gen 2 (Proxy)
    • RB5 (Proxy)

    Supported IoT Chipsets

    • Qualcomm® QCS6490
    • Qualcomm® QCS8250
    • Qualcomm® QCS8550