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### Software: Demos and Source Code

Please Note: where possible we make source code available for our prototypes under the GNU General Public License (GPL). LgEval and CROHMELib are made available under a non-commercial Creative Commons license.

#### DPRL Natural Scene Text Detector

(S. Zhu, Apr. 2016) [ We've identified issues with this code, and are working to resolve them. ]. The code below was used to produce the results published in Siyu Zhu's 2016 CVPR paper, A Text Detection System for Natural Scenes with Convolutional Feature Learning and Cascaded Classification, which obtained state-of-the-art results on the ICDAR 2015 Focused Scene Text Detection task at the time of publication.

#### Mathematical Information Retrieval

• Tangent-S (July 2017, by K. Davila, R. Zanibbi, A. Kane and F. Wm. Tompa). This version of the Tangent formula search engine supports individual and parallel search of formula appearance and semantics. This version extends Tangent v. 0.3.1 below, and is described in our SIGIR 2017 paper.

• Tangent v. 0.3.1 (May 2016, by K. Davila, R. Zanibbi, A. Kane and F. Wm. Tompa). This is the version described in our NTCIR-12 competition paper, with wildcard support for full subexpressions, and better separation of code for scoring metrics and locating subexpressions with the best match.

• Tangent v. 0.3 (July 2015, by R. Zanibbi, K. Davila, A. Kane and F. Wm. Tompa). You can download the source code and sample results (including .html pages with highlighted hits) below. This is the version described in our SIGIR 2016 paper.

• Tangent v. 0.2 (2014). Nidhin Pattaniyil implemented this extension of the Tangent system to support matrices and prefix subscripts and superscripts. This updated Tangent combines math expression retrieval with a Solr/Lucene text retrieval system, supporting mixed math and text queries.

Please Note: the files below are quite large, in part so that others have a better chance to replicate our results at NTCIR-11 (2014; NTCIR-11 paper)

• Tangent v. 0.1 demo (2013). A math expression search engine create by David Stalnaker. This online demo searches math expressions in an earlier version of English Wikipedia.
• ${m}_{\mathrm{in}}$ multimodal math search interface (2011-2015, demo). Supports mouse/touch, keyboard, mouse and (limited) image input). The program runs on tablets, desktops and laptops.
• Interface source code: GitHub Page
• Source code for recognition and other server applications used:
• The handwritten symbol recognizer used by min is available below.
• The image-based symbol recognizer source code is available from GitHub

• Freehand Formula Entry System (FFES) and DRACULAE handwritten math parser (1999 - 2007); early pen-based equation editor (last release: Aug. 10, 2007)

#### CROHME Handwritten Math Recognition Competitions (web page)

• IAPR TC11 CROHME Web Page (datasets and evaluation tools)
• CROHME InkML file viewer (source code provided with CROHMELib below)
• Handwritten math symbol recognizers (source code)
• Kenny Davila's System (SVM/Random Forest-based using offline-style features, 2014)
• Lei Hu's System (HMM-based using online features, 2011) - currently used for ${m}_{\mathrm{in}}$
• Complete systems submitted by the dprl (the 'RIT' team) for the competition:
• Early tools (2011) developed during the lab's participation in the first CROHME (R. Pospesel and K. Hart)

#### US Patent Office (USPTO) Figure and Part Label Detection Competition

• Paper co-authored by Chris Riedl (Northeastern, former Harvard post-doc), Marti Hearst (UC Berkeley), Siyu Zhu, Richard Zanibbi and researchers from the Harvard-NASA Tournament Lab (Karim Lakhani et al.) describing an online competition for labeling parts in US patent diagram images has been posted on the arXiv.

• The data and source code for the top-5 placing systems in the competition are available through the UCI Machine Learning Repository.

#### Evaluation Tools

• LgEval: the Label Graph Evaluation library (by R. Zanibbi and H. Mouchere). The library uses labeled directed graphs to represent results for structural pattern recognition tasks. To obtain the current version, issue the following command using git: