@inproceedings{4a22bb424c5a4755bc502396579043bc,
title = "Math expression image retrieval via attention-based framework",
abstract = "Math expression image retrieval concerns not only visual features but also high-level semantic understanding. Considering math expression image retrieval as traditional content-based image retrieval may suffer the layout misunderstanding, as math expressions with same symbols but different layouts may be interpreted as different meaning. In this paper, we propose a novel retrieval indexing framework for math expression retrieval, namely Scanner-Recognizer-Embedding (SRE) framework. The math expression images passed through SRE are projected into a low dimension semantic space. Retrieval based on embedded semantic vectors is fast and accurate. Experiments on a math expression database demonstrate that the SRE framework outperforms state-of-the-art image-based features.",
keywords = "Attention Mechanism, Image Retrieval, Math Expression",
author = "Caili Wu and Zhao Zhou and Hao Ye and Jing Yang and Liang He",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 31st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2019 ; Conference date: 04-11-2019 Through 06-11-2019",
year = "2019",
month = nov,
doi = "10.1109/ICTAI.2019.00044",
language = "英语",
series = "Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI",
publisher = "IEEE Computer Society",
pages = "259--264",
booktitle = "Proceedings - IEEE 31st International Conference on Tools with Artificial Intelligence, ICTAI 2019",
address = "美国",
}