PhyCV is the first computer vision library which utilizes algorithms directly derived from the equations of physics governing physical phenomena. The algorithms appearing in the first release emulate the propagation of light through a physical medium with natural and engineered diffractive properties followed by coherent detection. Unlike traditional algorithms that are a sequence of hand-crafted empirical rules, physics-inspired algorithms leverage physical laws of nature as blueprints. In addition, these algorithms can, in principle, be implemented in real physical devices for fast and efficient computation in the form of analog computing.[1] Currently PhyCV has three algorithms, Phase-Stretch Transform (PST) and Phase-Stretch Adaptive Gradient-Field Extractor (PAGE), and Vision Enhancement via Virtual diffraction and coherent Detection (VEViD). All algorithms have CPU and GPU versions. PhyCV is now available on GitHub and can be installed from pip.
^Physics-based Feature Engineering. Jalali et al. Optics, Photonics and Laser Technology, 2019
PhyCV is the first computer vision library which utilizes algorithms directly derived from the equations of physics governing physical phenomena. The...
improved to support GPU acceleration. In May 2022, it became one algorithm in PhyCV: the first physics-inspired computer vision library. Edge detection Feature...
identical chains (A and B). Each chain has a PAS domain, GAF domain and PHY domain. Domain arrangements in plant, bacterial and fungal phytochromes are...
{\operatorname {Var} (ISI)}{(\operatorname {E} [ISI])^{2}}}=CV^{2},} where C V {\displaystyle CV} is the coefficient of variation of ISI. Some neurons are...
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In electrochemistry, cyclic voltammetry (CV) is a type of potentiodynamic measurement. In a cyclic voltammetry experiment, the working electrode potential...
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there is a relation between charge and voltage, Q = C V {\displaystyle Q=CV} . As explained above, we can divide the voltage into two pieces: The galvani...
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