Pattern 1914 Enfield | Recognition of same-sex unions in Germany | pattern matching | Pattern 1853 Enfield | Facial recognition system | Pattern 1908 and 1912 cavalry swords | pattern | IEEE Transactions on Pattern Analysis and Machine Intelligence | Bloodstain pattern analysis | Beyond Recognition | Widmanstätten pattern | Universal Camouflage Pattern | Treaty of Recognition of Venezuela's Independence | The Pattern | Splinter pattern camouflage | Self-Destructive Pattern | Scrum pattern | Recognition of same-sex unions in the Republic of Ireland | Recognition of same-sex unions in Romania | Recognition of same-sex unions in Ireland#The 'KAL' recognition case | Recognition of prior learning | radiation pattern | Pattern welding | ''Pattern Recognition'' | Pattern matching | Pattern (devotional) | Pattern (architecture) | Pattern and Decoration | Pathogen-associated molecular pattern | Outline of object recognition |
The Curta is referenced in chapter four of William Gibson's Pattern Recognition.
For example, data binning may be used when small instrumental shifts in the spectral dimension from MS or NMR experiments will be falsely interpreted as representing different components, when a collection of data profiles is subjected to pattern recognition analysis.
Sanjeev Ramesh Kulkarni (born Mumbai, India, September 21, 1963) is Professor of Electrical Engineering at Princeton University, where he teaches and conducts research in a broad range of areas including statistical inference, pattern recognition, machine learning, information theory, and signal/image processing.
N. Srihari (Sargur Narasimhamurthy Srihari) is an American Computer scientist and educator who has made contributions to the field of pattern recognition.
Research in his laboratory includes the development and application of k-nearest neighbor pattern recognition methods to the field of QSARs and application of the Delaunay tessellation technique to protein structure analysis.
Cayce Pollard, protagonist of William Gibson's 2003 novel Pattern Recognition
A meticulous record keeper, Hoadley taught himself meteorology and developed a pattern recognition based forecasting method, primarily using surface data.
His Synchonous Matching Adaptive Resonance Theory (SMART) model shows spiking laminar cortical circuits self-organize and stably learn relevant information, and how these circuits be embedded in low-power, memristor based hybrid CMOS chip and used to solve challenging pattern recognition problems.