FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms we found to work best for nearest neighbor search and a system for automatically choosing the best algorithm and optimum parameters depending on the dataset. FLANN is written in C++ and contains bindings for the following languages: C, MATLAB and Python.
Keywords for this software
References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Rachkovskij, D.A.: Index structures for fast similarity search for real-valued vectors. I (2018)
- Rachkovskij, D.A.: Binary vectors for fast distance and similarity estimation (2017)
- Yue, Xiaodong; Chen, Yufei; Miao, Duoqian; Qian, Jin: Tri-partition neighborhood covering reduction for robust classification (2017)
- Rachkovskij, D.A.: Real-valued embeddings and sketches for fast distance and similarity estimation (2016)
- Wang, Tianyang; Wüchner, Roland; Sicklinger, Stefan; Bletzinger, Kai-Uwe: Assessment and improvement of mapping algorithms for non-matching meshes and geometries in computational FSI (2016)
- Xiao, Bo; Biros, George: Parallel algorithms for nearest neighbor search problems in high dimensions (2016)
- Nivoliers, Vincent; Lévy, Bruno; Geuzaine, Christophe: Anisotropic and feature sensitive triangular remeshing using normal lifting (2015)
- Emiris, Ioannis Z.; Fisikopoulos, Vissarion: Efficient random-walk methods for approximating polytope volume (2014)
- Henry, Christopher; Peters, James F.: Arthritic hand-finger movement similarity measurements: tolerance near set approach (2011)
Further publications can be found at: http://www.cs.ubc.ca/research/flann/#publications