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Tree Annotations in LiDAR Data Using Point Densities and Convolutional Neural Networks
The third method is a scaled version of the PointNet++ method and works directly on outdoor point clouds and achieves an F_score of 82. 1% on the ISPRS benchmark dataset, comparable to the state-of-the-art methods but with increased efficiency.
It All Matters: Reporting Accuracy, Inference Time and Power Consumption for Face Emotion Recognition on Embedded Systems
In this paper, we identify the state-of-the art face emotion recognition methods that are potentially suitable for embedded environment and the most frequently used datasets for this task.
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