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Last Updated: 05/18/2021
Convert and optimize a U-Net-based model for brain tumor segmentation to maximize inference performance on Intel® architecture.
Accelerate object detection by using asynchronous inferencing and distributing workloads to multiple types of processing units.
Build a solution to analyze customer expressions and reactions to product advertising positioned on retail shelves.
Run inference on a pre-trained people detection model from the Intel Distribution of OpenVINO™ toolkit to detect people in a retail setting.
Perform object detection and inference with multiple video and image input feeds simultaneously. Monitor customer activity and track product inventory using a pretrained neural network.
Classify the probability of pneumonia in x-ray images using a pretrained neural network and the Intel® Distribution of OpenVINO™ toolkit. Use Class Activation Maps for insight into network decisions.
Build a modular GStreamer* pipeline to perform object detection, tracking, and classification using the Intel® Distribution of OpenVINO™ toolkit.
Learn how to use DevCloud's benchmarking tool to evaluate the performance of your model's synchronous and asynchronous inference.
Restyle images and video frames using a pretrained network and the Intel® Distribution of OpenVINO™ toolkit.
Perform object detection on images and video using a pretrained network and the Intel® Distribution of OpenVINO™ toolkit.
Migrate your IoT application from DevCloud to your local edge device.