AI art innovation/ clustering body shape recognition (ML)

from AI art innovation/ clustering body shape recognition (ML)

AI art innovation/ clustering body shape recognition (ML)

AI research leads to Body Shape & color unsupervised recognition that does not require the prior knowledge of class membership (Hartigan). This approach develops algorithms that construct classes as the analyzed forms are considered. They are called grouping algorithms or clustering – a machine learning technique. Machine learning ML uses a type technique named unsupervised learning, which finds hidden patterns or intrinsic structures in input data. Choosing the right algorithm can seem overwhelming – there are dozens unsupervised machine learning algorithms, and each takes a different approach to learning (hybrid human-machine)

Simnon – Every system, which can be defined in mathematical terms, a discrete event simulation is the simulation of queues and operating systems. Simnon is intended for the simulation/ emu

lation of continuous time as well as discrete time dynamical

systems. Numerical integration routines are used to simulate differential equations. = algorithms IoT –Internet of Things is a system of interrelated computing devices, mechanical and digital machines, objects or people

CLUSTERING algorithm #bodyshape recognition (Hartigan, Vanea) CLUSTERING algorithm #color recog - nition / filters, noise removal (Wiener), restoration of geometric distortions (Sil - verman)