Influence of Color Noise on Processing of Optical Signals by Swarm Intellect Algorithm

An approach based on stochastic particle swarm optimization was applied for the mathematical processing of spectral profiles with noise. To test the algorithm’s stability with respect to noise, we used the noises with different values of the Hurst index which characterizes noise component from the point of view of prevalence of low-frequency or high-frequency component in it. The Hurst index varied from 0.1 to 0.9. An influence of color noise with level from 1 to 10% on processing of optical signals by particle swarm optimization algorithm was analyzed. This method is shown to be stable with respect to noise with the level of 10% if it’s the Hurst index does not exceed the value of 0.5

Finding key points in a hand image using heatmaps

© Published under licence by IOP Publishing Ltd. This paper presents an approach to finding key points in the image of a hand using heat maps. For this, a convolutional model of a neural network and a training method on heatmaps were combined. An open bank of palm photos, supplemented by a set of own images and synthetic data, was used as a dataset. Direct and inverse transformations of two-dimensional coordinates on the plane into heat maps with a 2D Gaussian function centered at coordinate points were applied, data was prepared, the model was trained and tested. As a result of this approach, a neural network model able to recognise real world images was obtained