Bob: a free signal processing and machine learning toolbox for researchers
| Type of publication: | Conference paper |
| Citation: | Anjos_Bob_ACMMM12 |
| Publication status: | Published |
| Booktitle: | Proceedings of the ACM Multimedia Conference |
| Year: | 2012 |
| Month: | October |
| Crossref: | Anjos_Idiap-RR-25-2012: |
| URL: | https://www.idiap.ch/software/b... |
| Abstract: | Bob is a free signal processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, Switzerland. The toolbox is designed to meet the needs of researchers by reducing development time and efficiently processing data. Firstly, Bob provides a researcher-friendly Python environment for rapid development. Secondly, efficient processing of large amounts of multimedia data is provided by fast C++ implementations of identified bottlenecks. The Python environment is integrated seamlessly with the C++ library, which ensures the library is easy to use and extensible. Thirdly, Bob supports reproducible research through its integrated experimental protocols for several databases. Finally, a strong emphasis is placed on code clarity, documentation, and thorough unit testing. Bob is thus an attractive resource for researchers due to this unique combination of ease of use, efficiency, extensibility and transparency. Bob is an open-source library and an ongoing community effort. |
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TABULA RASA BEAT |
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| Added by: | [UNK] |
| Total mark: | 0 |
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