计算机科学
水准点(测量)
人工智能
可视化
凝视
对象(语法)
反向传播
突出
序列(生物学)
目标检测
机器翻译
图像(数学)
人工神经网络
机器学习
计算机视觉
模式识别(心理学)
生物
遗传学
地理
大地测量学
作者
Kelvin Xu,Jimmy Ba,Ryan Kiros,Kyunghyun Cho,Aaron Courville,Ruslan Salakhudinov,Rich Zemel,Yoshua Bengio
出处
期刊:International Conference on Machine Learning
日期:2015-07-06
卷期号:3: 2048-2057
被引量:6784
摘要
Inspired by recent work in machine translation and object detection, we introduce an attention based model that automatically learns to describe the content of images. We describe how we can train this model in a deterministic manner using standard backpropagation techniques and stochastically by maximizing a variational lower bound. We also show through visualization how the model is able to automatically learn to fix its gaze on salient objects while generating the corresponding words in the output sequence. We validate the use of attention with state-of-the-art performance on three benchmark datasets: Flickr9k, Flickr30k and MS COCO.
科研通智能强力驱动
Strongly Powered by AbleSci AI