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Aug, 2017
改进视觉问答模型的收敛和准确性的简单损失函数
A Simple Loss Function for Improving the Convergence and Accuracy of Visual Question Answering Models
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Ilija Ilievski, Jiashi Feng
TL;DR
本研究提出软交叉熵损失函数来解决在视觉问答过程中模型训练精度和损失准确度之间的差异问题, 实验证明该方法可提升模型精度高达 1.6%.
Abstract
visual question answering
as recently proposed
multimodal learning
task has enjoyed wide attention from the deep learning community. Lately, the focus was on developing new representation fusion methods and atten
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