In this paper, we propose a novel data-augmentation approach to handle samples with rotation, which utilizes the distribution of the object's orientation ...

SR-POD: Sample Rotation based on Principal-axis Orientation. Distribution for Data Augmentation in Deep Object Detection. Dr Jinchang Ren. Department of ...

This work creates a differentiable approximation of label accuracy and introduces Rotation Uncertainty (RU) Loss, allowing the model to adapt to the ...

In this paper, we propose a novel data-augmentation approach to handle samples with rotation, which utilizes the distribution of the object's orientation ...

Aug 27, 2018 · In this paper, we propose a novel data-augmentation approach to handle samples with rotation, which utilizes the distribution of the object's ...

SR-POD: Sample Rotation based on Principal-axis Orientation Distribution for Data Augmentation in Deep Object Detection. Article. Jul 2018; COGN SYST RES.

Jun 15, 2024 · You haven't rotations to your input data as part of data augmentation? This is the most common way to make classifiers agnostic to rotations.

Readers: Everyone. SR-POD: Sample rotation based on principal-axis orientation distribution for data augmentation in deep object detection · hmtl icon · Yue Xi ...

SR-POD: Sample rotation based on principal-axis orientation distribution for data augmentation in deep object detection · Computer Science. Cognitive Systems ...

Sr-pod: sample rota- tion based on principal-axis orientation distribution for data augmentation in deep object detection. Cog- nitive Systems Research, 52 ...