Abstract The problem of matching point clouds is an efficient way registration, which significant for many research fields including computer vision, machine learning, and robotics. There may be linear or non-linear transformation between clouds, but determining the affine relation more challenging among cases. Various methods have been presented to overcome this in literature one them variant ...

To analyze marine animals behavior, seasonal distribution and abundance, digital imagery can be acquired by visual or Lidar camera. Depending on the quantity and properties of acquired imagery, the animals are characterized as either features (shape, color, texture, etc.), or dissimilarity matrices derived from different shape analysis methods (shape context, internal distance shape context, et...

It is still a challenging task to segment real-world images, since they are often distorted by unknown noise and intensity inhomogeneity. To address these problems, we propose a novel segmentation algorithm via a local correntropy-based K-means (LCK) clustering. Due to the correntropy criterion, the clustering algorithm can decrease the weights of the samples that are away from their clusters. ...

In this paper, we study signal detection in multi-input-multi output (MIMO) communications system with non-Gaussian noises such as Middleton Class A noise, Gaussian mixtures and alpha stable distributions, using several deep neural network-based detector models FULLYCONNECTED DETNET detector. By applying information theoretic criterion of Maximum Correntropy , SVD analysis on the channel matrix...

Background and Aim Image registration alignment are the main limitations of augmented reality (AR)-based knee replacement surgery. This research aims to decrease error, eliminate outcomes that trapped in local minima improve problems, handle occlusion maximize overlapping parts. Methodology Markerless image method was used for AR-based surgery guide visualize surgical operation. While weight le...