PathS: Enhancing Geographical Maps with Environmental Sensed Data
By Armir Bujari, Matteo Ciman, O. Gaggi, Gustavo Marfia, C. Palazzi. MobileHealth@MobiHoc, 2015
386 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Transportation
View Paper: https://www.semanticscholar.org/paper/10af5e2fb348d2addf1d446eeaf5e541aeb64cf2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
In Electrical and Electronic Engineering
- Steven S. Skiena
- Jacques Verstraëte
- Steven T. Flammia
- Alexandre Blais
- Benjamin J. Brown
- Andreas Wallraff
In Transportation
Citations in the corpus
- Extremal problems for cycles in graphs (2016, background): “The following conjecture is due to Thomassen [125]: Conjecture VII.”
- Realizing repeated quantum error correction in a distance-three surface code (2021, methodology): “We decode the error syndromes using a minimum-weight perfect matching algorithm [48, 49].”
- Demazure Modules, Fusion Products and Q-Systems (2013, background): “On the other hand it was known that D(1, lω) is also of dimension 2 l ([19],[27],[28]) which shows that Wloc(lω) ∼= D(1, lω).”
- Valence Bonds in Random Quantum Magnets: Theory and Application to YbMgGaO4 (2017, methodology): “We computed the complete dimer covering with minimum dimer energy using the famous blossom algorithm of Edmond [171,172] as implemented in the NetworkX PYTHON package (implementation by van Rantwijk, “max_weight_matching”with “maxcardinality 1⁄4 True”; weights are interpreted as negative energies).”
- The Algorithm Design Manual (2020, methodology): “Edmond’s algorithm [Edm65] for maximum-cardinality matching is of great historical interest for provoking questions on what problems can be solved in polynomial time.”
- The XZZX surface code (2020, methodology): “Having demonstrated the remarkable code-capacity 253 thresholds of the XZZX code, we now demonstrate how 254 to translate these high thresholds into practice using a 255 matching decoder [14, 37, 38].”