Stanford University

SEMINAR SERIES

Melissa Dell
LayoutParser: A Unified Toolkit for Deep Learning-Based Document Image Analysis

Melissa Dell: LayoutParser: A Unified Toolkit for Deep Learning-Based Document Image Analysis
October 4, 2021
12p - 1p Pacific Time
Virtual Event
Free
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Join us on Monday, October 4, for our first Seminar Series of the fall 2021 semester. Professor Melissa Dell of Harvard University will join S-DEL Director Erik Brynjolfsson to discuss of LayoutParser, an open-source library for streamlining the usage of DL in DIA research and applications.

This is a free, virtual event open to everyone. There will be a brief Q&A following the discussion.


Abstract

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

Zejiang Shen, Ruochen Zhang, Melissa Dell, Benjamin Charles Germain Lee, Jacob Carlson, and Weining Li

Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production and extended for further investigation. However, various factors like loosely organized codebases and sophisticated model configurations complicate the easy reuse of important innovations by a wide audience. Though there have been ongoing efforts to improve reusability and simplify deep learning (DL) model development in disciplines like natural language processing and computer vision, none of them are optimized for challenges in the domain of DIA. This represents a major gap in the existing toolkit, as DIA is central to academic research across a wide range of disciplines in the social sciences and humanities. This paper introduces LayoutParser, an open-source library for streamlining the usage of DL in DIA research and applications. The core LayoutParser library comes with a set of simple and intuitive interfaces for applying and customizing DL models for layout detection, character recognition, and many other document processing tasks. To promote extensibility, LayoutParser also incorporates a community platform for sharing both pre-trained models and full document digitization pipelines. We demonstrate that LayoutParser is helpful for both lightweight and large-scale digitization pipelines in real-world use cases. The library is publicly available here.


About Melissa Dell

Professor Melissa Dell is the Andrew E. Furer Professor of Economics at Harvard University. She is the 2020 recipient of the John Bates Clark Medal, awarded each year to an American economist under the age of forty who is judged to have made the most significant contribution to economic thought and knowledge. In 2018, The Economist named her one of the decade’s eight best young economists, and in 2014 she was named by the IMF as the youngest of 25 economists under the age of 45 shaping thought about the global economy.

Her research focuses on economic growth and political economy. She has examined the factors leading to the persistence of poverty and prosperity in the long run, the effects of trade-induced job loss on crime, the impacts of U.S. foreign intervention, and the effects of weather on economic growth. She has also developed deep learning-powered methods for curating social science data at scale, released in the open-source package Layout Parser. This work supports many of her current projects, which rely on digitizing historical sources far too large for manual digitization.

Professor Dell is a senior scholar at the Harvard Academy for Area and International Studies and a research associate at the National Bureau of Economic Research. She received an AB in Economics from Harvard in 2005, an MPhil in Economics from Oxford in 2007, and a PhD in Economics from MIT in 2012. Before joining the Harvard Economics department in 2014, she was a Junior Fellow at the Harvard Society of Fellows.

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