When studying the results of a segmentation algorithm using convolutional neural networks, one wonders about reliability and consistency results. This leads to questioning possibility such an in applications where there is little room for doubt. We propose this paper new attention gate based on use Chan-Vese energy minimization control more precisely masks given by standard CNN architecture as ...

This paper introduces a novel approach deploying the mechanism of ‘attention’ by adapting a swarm intelligence algorithm – Stochastic Diffusion Search – to selectively attend to detailed areas of a digital canvas. Once the attention of the swarm is drawn to a certain line within the canvas, the capability of another swarm intelligence algorithm – Particle Swarm Intelligence – is used to produce...

Aiming at the problems of low detection accuracy for objects with non-significant features in FCOS network, a new object method based on attention mechanism is proposed to improve performance which can effectively guide network focus detailed features. According verification experimental results KITTI dataset, AP value improved mechanism-based car and person by 1.1% 4.9% compared standard respe...

At present, traditional facial expression recognition methods of convolutional neural networks are based on local ideas for feature expression, which results in the model’s low efficiency capturing dependence between long-range pixels, leading to poor performance recognition. In order solve above problems, this paper combines a self-attention mechanism with residual network and proposes new mod...