论文标题
深图像方向角度检测
Deep Image Orientation Angle Detection
论文作者
论文摘要
估计和纠正任何图像的方向角度是一项非常具有挑战性的任务。最初的工作将手工工程功能用于此目的，在发明基于卷积的神经网络的深度学习之后，该问题显示出显着改善。但是，本文表明，CNN和专门为角度设计的自定义损失函数的组合带来了最新的结果。这包括任何程度（0至360度）的任何图像或文档的方向角度估计，
Estimating and rectifying the orientation angle of any image is a pretty challenging task. Initial work used the hand engineering features for this purpose, where after the invention of deep learning using convolution-based neural network showed significant improvement in this problem. However, this paper shows that the combination of CNN and a custom loss function specially designed for angles lead to a state-of-the-art results. This includes the estimation of the orientation angle of any image or document at any degree (0 to 360 degree),
