Low Power Image Recognition: The Challenge Continues

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Many mobile systems (smartphones, electronic glass, autonomous robots) can capture images. These systems use batteries and energy conservation is essential. This challenge aims to discover the best technology in both image recognition and energy conservation. Winners will be evaluated based on both high recognition accuracy and low power usage. Image recognition involves many tasks. This challenge focuses on object detection, a basic routine in many recognition approaches. The following two examples illustrate the task. In the first example, there are two objects: a bird and a frog. In the second example, there are several objects: cars, persons, motorcycle, and a helmet. The training and validation data for LPIRC comes from the ImageNet Large Scale Visual Recognition Challenge detection competition. The test data will be specific to LPIRC.

Many mobile systems (smartphones, electronic glass, autonomous robots) can capture images. These systems use batteries and energy conservation is essential. This challenge aims to discover the best technology in both image recognition and energy...

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