This page lists both works that have been published about the Accord.NET Framework, as well as published works that have used, reference, or otherwise include a mention to the framework.

Technical reports

  • Souza, C.R., " A Tutorial on Principal Component Analysis with the Accord.NET Framework ". Department of Computing, Federal University of Sao Carlos. arXiv:1210.7463. Technical Report, 2012
    A technical report and a complete tutorial on Principal Component Analysis, a common and popular dimensionality reduction technique found in many real-world solutions. This report aims not only to explain PCA in the same molds as given by Lindsay I Smith, but to present many of the features of the Accord.NET Framework which can help performing this analysis.

Academic publications

The following papers include at least a citation to the framework, reference material published based on the framework or have used standalone code which now has been incorporated in the framework. Some of those have been found using search engines or automatic alerts. If you would like to include your paper, or if your paper has been incorrectly incorporated in this collection, please let me know.

  1. Bartosz Papis, Evaluation of Colour Recognition Algorithms with a Palette Designed for Applications which Aid People with Visual Impairment . In: International Journal of Image, Graphics and Signal Processing (IJIGSP), DOI: 10.5815/ijigsp.2014.12.01, 2014.
  2. T. Roushan, D. Chaki, A. M. H. Ali, Predicting Untranslated Regions and Code Sections in DNA using Hidden Markov Models . International Journal of Computer and Information Technology (ISSN: 2279 – 0764), Volume 03 – Issue 05, September 2014.
  3. Hogland, John S.; Anderson, Nathaniel M. Improved analyses using function datasets and statistical modeling . In: Proceedings of the 2014 ESRI Users Conference; July 14-18, 2014, San Diego, CA. Redlands, CA: Environmental Systems Research Institute. 2014.
  4. Laxpati, Nealen G. et al. Real-Time in Vivo Optogenetic Neuromodulation and Multielectrode Electrophysiologic Recording with NeuroRighter . Frontiers in Neuroengineering 7 (2014): 40. PMC. Web. 24 Dec. 2014.
  5. Svilen Dimitrov, Framework for Analyzing Sounds of Home Environment for Device Recognition . Department of Computer Science at Saarland University, German Research Center for Artificial Intelligence - DFKI. Master's thesis, 2014.
  6. Michael D. Moore, Development and Resultant Implementation of Custom Software for Analyses of Galactic Neighborhoods . West Virginia University. Master thesis, 179 pages, 2014.
  7. Veyel D, Erban A, Fehrle I, Kopka J, Schroda M. Rationales and Approaches for Studying Metabolism in Eukaryotic Microalgae . Metabolites; 4(2):184-217. 2014.
  8. Karimi, Behnam. An automatic system for classification of breast cancer lesions in ultrasound images . PhD thesis, Concordia University, 2014.
  9. Boffo, Sandra: Assistenzsysteme mit Emotionserkennung. Prototypische Realisierung mit Betrachtung der ethischen Dimension . University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Student Thesis No. 2450 (2014).
  10. Simon Ruffieux, Denis Lalanne, Elena Mugellini, Omar Abou Khaled, Gesture recognition corpora and tools: A scripted ground truthing method . Computer Vision and Image Understanding, Volume 131, February 2015, Pages 72-87, ISSN 1077-3142, 2014.
  11. N. Dhaubhadel, S. Subedi, S. Sagar Dongol, ANFA Database and Prediction System , Group project for the Bachelor of Computer Science and Information Technology, St. Xavier‘s College. Maitighar, Kathmandu, 2014.
  12. Steenbergen, N. Predicting glucose concentration in type 1 diabetes patients using artificial neural networks . Faculty of Humanities Theses, Bachelor thesis, 2014.
  13. Z. Zhong, Y. Peng, X. Li, D. Zhou, Color Balance and Seam-line Removal for Multi-camera Stitching Image , JNIT: Journal of Next Generation Information Technology, Vol. 5, No. 2, pp. 47 ~ 55, 2014
  14. M. Kolařík, R. Jašek, Z. K. Oplatková, Maximizing Vector Distances for Purpose of Searching—A Study of Differential Evolution Suitability , Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014 Advances in Intelligent Systems and Computing Volume 303, 2014, pp 419-428.
  15. A. G. Alex, S. Jegatha, J. G. Jayanthi; S. A. Rabara, SaaS Framework for Library Augmented Reality Application , 2014 World Congress on Computing and Communication Technologies (WCCCT), 2014.
  16. Phua, Yee Ling. Social media sentiment analysis and topic detection for Singapore English . Monterey, California. Naval Postgraduate School. Master thesis, September 2013.
  17. H. Josiński, A. Świtoński, A. Michalczuk, D. Kostrzewa, K. Wojciechowski. Human Identification Based on Gait Video Sequences , In: Proceedings of the International Conference on Computer Science and Engineering, p. 312-317, 2013
  18. Daniel Thuerck, Developing an Linguistic Forensics System and Providing useful NLP Data Visualizations . Lab Project - Final Report, Oct. 9, 2013.
  19. H. Josiński, D. Kostrzewa, A. Michalczuk, A. Świtoński, K. Wojciechowski. Feature Extraction and HMM-based Classification of Gait Video Sequences for the Purpose of Human Identification . In: Vision Based Systems for UAV Applications. Studies in Computational Intelligence Volume 481, 2013, pp 233-245.
  20. C. Schneider, A. Barker, and S. Dobson. Autonomous Fault Detection in Self-Healing Systems: Comparing Hidden Markov Models and Artificial Neural Networks . In Proceedings of International Workshop on Adaptive Self-tuning Computing Systems (ADAPT '14). ACM, New York, NY, USA, 2014.
  21. B. Blamey, T. Crick, G. Oatley. The First Day of Summer: Parsing Temporal Expressions with Distributed Semantics . Research and Development in Intelligent Systems XXX, pp 389-402, 2013. DOI: 10.1007/978-3-319-02621-3_29
  22. L. Angelini, F. Carrino, S. Carrino, M. Caon, D. Lalanne, O. A. Khaled, and E. Mugellini. Opportunistic synergy: a classifier fusion engine for micro-gesture recognition . Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI), Pages 30-37, ACM New York, NY, USA, 2013. DOI: 10.1145/2516540.2516563
  23. W. Mueller, K. Nowakowski, R. J. Tomczak, S. Kujawa, J. Rudowicz-Nawrocka, P. Idziaszek, A. Zawadzki; IT system supporting acquisition of image data used in the identification of grasslands . Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88781T (July 19, 2013); doi:10.1117/12.2031602.
  24. Senn, Fabian and Lam, Cyrill. Selbstlernende Software zur Analyse von Texten . Bachelor thesis, HSR Hochschule für Technik Rapperswil (2013).
  25. J. G. Arriaga, G. Kossan, M. L. Cody, E. E. Vallejo, C. E. Taylor. Acoustic sensor arrays for understanding bird communication. Identifying Cassin's Vireos using SVMs and HMMs. ADVANCES IN ARTIFICIAL LIFE, ECAL 2013 DOI:
  26. Hossein Javidnia, Mohammad Amiri and Seyed Iman Meshkat. Article: H.M.C.R Fingerprint Matching. International Journal of Computer Applications 65(6):16-24, March 2013. Published by Foundation of Computer Science, New York, USA.
  27. Keramitsoglou, I.; Kiranoudis, C.T.; Qihao Weng, "Downscaling Geostationary Land Surface Temperature Imagery for Urban Analysis," Geoscience and Remote Sensing Letters, IEEE , vol.10, no.5, pp.1253,1257, Sept. 2013 DOI: 10.1109/LGRS.2013.2257668
  28. M. H. Afif, A-R. Hedar, T. H. A. Hamid, Y. B. Mahdy; SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis; International Journal of Advanced Computer Science and Applications, Vol. 4, No. 2, 2013
  29. M. Lidegaard. Development of a Head Mounted Device for Point-of-Gaze Estimation in Three Dimensions, Master thesis. University of Southern Dernmark, 2012.
  30. Caon, M.; Tscherrig, J.; Yong Yue; Khaled, O.A.; Mugellini, E., "Extending the interaction area for view-invariant 3D gesture recognition," Image Processing Theory, Tools and Applications (IPTA), 2012 3rd International Conference on , vol., no., pp.293,298, 15-18 Oct. 2012
  31. M. Afif, A-R. Hedar, Data Classification Using Support Vector Machine Integrated With Scatter Search Method, Proceedings of the 2012 Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC 2012), Article number 6186977, Pages 168-172, Alexandria, 6-9 March 2012.
  32. M. Afif, A-R. Hedar, T. H. Abdel Hamid, Y. B. Mahdy, Support Vector Machines With Weighted Powered Kernels For Data Classification, The first International Conference on Advanced Machine Learning Technologies and Applications (AMLTA12), 2012. Available on
  33. M. Afif, A-R. Hedar, T. H. Abdel Hamid, Y. B. Mahdy, Parameter Determination Of Support Vector Machine Using Scatter Search Approach, The 22nd International Conference on Computer Theory and Applications (ICCTA 2012), 2012.
  34. Eli T. Brown, Jingjing Liu, Carla E. Brodley, Remco Chang. Dis-Function: Learning Distance Functions Interactively. To appear in the Proceedings of the IEEE Conference on Visual Analytics Science and Technology, 2012.
  35. Guido Soetens, Estimating the limitations of single-handed multi-touch input. Master Thesis, Utrecht University. September, 2012.
  36. K. N. Pushpalatha, A. K. Gautham, D. R. Shashikumar, K. B. ShivaKumar. Iris Recognition System with Frequency Domain Features optimized with PCA and SVM Classifier, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 5, No 1, September 2012.
  37. Reza Taherkhani, Mohammad Kia. Designing a high accuracy 3D auto stereoscopic eye tracking display, using a common LCD monitor. Journal of 3D Research, July 2012, 3:2.
  38. Arnaud Ogier, Thierry Dorval. HCS-Analyzer: Open source software for High-Content Screening data correction and analysis. Bioinformatics. First published online May 13, 2012.
  39. Ludovico Buffon, Evelina Lamma, Fabrizio Riguzzi, and Davide Forment. Un sistema di vision inspection basato su reti neurali. In Matteo Baldoni, Federico Chesani, Bernardo Magnini, Paola Mello, and Marco Montai, editors, Popularize Artificial Intelligence. Proceedings of the AI*IA Workshop and Prize for Celebrating 100th Anniversary of Alan Turing's Birth (PAI 2012), Rome, Italy, June 15, 2012, number 860 in CEUR Workshop Proceedings, pages 1-6, Aachen, Germany, 2012.
  40. Liam Williams, Spotting The Wisdom In The Crowds. Master Thesis on Joint Mathematics and Computer Science. Imperial College London, Department of Computing. June, 2012.
  41. Yaser Alosefer, Analysing Web-based Malware Behaviour through Client Honeypots. PhD Thesis. Cardiff University, School of Computer Science & Informatics, 2012.
  42. Le Hoang Thai,Tran Son Hai,Nguyen Thanh Thuy, "Image Classification using Support Vector Machine and Artificial Neural Network", IJITCS, vol.4, no.5, pp.32-38, 2012.
  43. Zavalnijs, A. Improving Interaction in a Musical Tutor for Playing by Ear . Master Thesis. School of Informatics, University of Edinburgh, 2011.
  44. D. A. Logsdon. Arm-Hand-Finger Video Game Interaction . Master's thesis, Texas A&M University, 2011.
  45. Almeida, R. N., Portuguese Sign Language Recognition via Computer Vision and Depth Sensor. Master Thesis. Lisbon University Institute, Department of Science and Information Technology. October, 2011.
  46. Alosefer, Y.; Rana, O.F.; "Predicting client-side attacks via behaviour analysis using honeypot data," Next Generation Web Services Practices (NWeSP), 2011 7th International Conference on , vol., no., pp.31-36, 19-21 Oct. 2011
  47. Brummitt, L. Scrabble Referee: Word Recognition Component, 2011. Final project report. University of Sheffield, Sheffield, England.
  48. Cani, V., 2011. Image Stitching for UAV remote sensing application. Master Degree Thesis. Computer Engineering, School of Castelldefels of Universitat Politècnica de Catalunya. Barcelona, Spain.
  49. Feuerstack, S., Colnago, J. H. and Souza, C. R.; Designing and Executing Multimodal Interfaces for the Web based on State Chart XML. Proceedings of 3a. Conferência Web W3C Brasil 2011, The 3rd W3C Brazil Web Conference, 17th-18th November, Rio de Janeiro, Brazil. 2011.
  50. Hassani, A. Z.; "Touch versus in-air Hand Gestures: Evaluating the acceptance by seniors of Human-Robot Interaction using Microsoft Kinect," Master Thesis, University of Twente, Enschede, Netherlands, 2011.
  51. Kaplan, K., 2011. ADES: Automatic Driver Evaluation System. PhD Thesis, Boğaziçi University, Istanbul, Turkey.
  52. Wright, M., Lin, C.-J., O'Neill, E., Cosker, D. and Johnson, P., 2011. 3D Gesture recognition: An evaluation of user and system performance. In: Pervasive Computing - 9th International Conference, Pervasive 2011, Proceedings. Heidelberg: Springer Verlag, pp. 294-313.
  53. Deinhofer, M., Roland L., Baca, A., 2010. Klassifizierung von Schlagtechniken im Badminton mittels Mustererkennung aus Inertialdaten. 13 Österreichische Sportwissenschaftliche Gesellschaft, Bruch an der Mur.
  54. Lourenço, J., 2010. Wii3D: Extending the Nintendo Wii Remote into 3D. Final course project report, Rhodes University, Grahamstown. 110p.
  55. Mendelssohn, T.; 2010. Gestureboard - Entwicklung eines Wiimote-basierten, gestengesteuerten, Whiteboard-Systems für den Bildungsbereich. Final project report. Hochschule Furtwangen University, Furtwangen im Schwarzwald, Germany.

Standalone software and projects

  • Virtual Beach 3 - Virtual Beach 3 is a is a decision support tool created by the United States Enviromental Protection Agency to construct site-specific statistical models to predict bacteria (FIB) concentrations at recreational beaches. The framework is listed as one of the technologies employed in its development.
  • PhotoCam by Gauss Development - PhotoCam software helps users choose the best eyeglasses. It is installed on specially made computers (panels with touch screens) in optical stores.
  • Point and Call - Windows phone application to read a phone number using the phone's camera. After reading the number, it is possible to either call or save this number in your contact list, useful for reading numbers from magazines or business cards.
  • Harperia - Language agnostic speech recognition. Uses AForge.NET and Accord.NET to process audio signals and recognize specific recordings using Neural Networks.
  • GMM-EM - Estimates parameters of a multidimensional Gaussian Mixture Model (GMM) by expectation-Maximization (EM) methods and performs Receiver Operating Characteristics (ROC) analysis based on given true labels of input vectors in medical research. Created in a time where GMMs were not yet available in Accord.NET, this project uses a combination of many libraries to achieve its goals.

Online resources

  • Haar-feature Object Detection in C# - A description of how it was possible to achieve real-time face detection with some clever ideas back in 2001.
  • Handwriting Recognition using Kernel Discriminant Analysis - Demonstration of handwritten digit recognition using Kernel Discriminant Analysis and the optical recognition of handwritten digits data set from the UCI Machine Learning Repository.
  • Handwriting Recognition Revisited: Kernel Support Vector Machines - In a previous article, we discussed how to perform the recognition of handwritten digits using Kernel Discriminant Analysis. In this article, we will discuss some techniques to do it using Kernel Support Vector Machines.
  • Automatic Image Stitching with Accord.NET - Demonstration of automatic image stitching by interest point matching using the Accord and AForge.NET Frameworks
  • Decision Trees in C# - Implementing and using Decision Trees in C#.
  • Gaussian Mixture Models and Expectation-Maximization - Gaussian Mixture Models (GMM) can be seen as a type of unsupervised learning or clustering methods. They are among the most statistically mature methods for clustering. But unlike K-Means, GMMs are able to build soft clustering boundaries, i.e., points in space can belong to any class with a given probability.
  • Kernel Principal Component Analysis in C# - KPCA is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non-linear mapping. This article details the method and its implementation in the Accord.NET Framework.

Preferred citation style

If you use Accord.NET Framework in your research, you are invited to cite the project in your publication. There are many advantages in clearly stating all tools used in a research, including the increased reproducibility and transparency which should be the goal of any serious academic publication. If you would like to accept this invitation and cite Accord.NET or any material published together the framework in your work, the preferred style of citation is:

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