The joint hyperspectral image (HSI) and light detection ranging (LiDAR) data classification aims to interpret ground objects at more detailed precise level. Although deep learning methods have shown remarkable success in the multisource task, self-supervised has rarely been explored. It is commonly nontrivial build a robust model for classification, due fact that semantic similarities of neighb...

Mouse dynamics authentication is a method for identifying person by analyzing the unique pattern or rhythm of their mouse movement. Owing to its distinctive properties, such movements can be used as basis security. The development technology followed urge keep private data safe from hackers. Therefore, increasing accuracy user classification and reducing false acceptance rate (FAR) are necessar...

The problem of feature transformation arises in many fields of information processing, including machine learning, data compression, computer vision and geosciences applications. Here we discuss an approach that seeks a hyperspherical coordinate system preserving geodesic distances in the high dimensional hyperspectral data space. A lower dimensional hyperspherical manifold is computed using a ...

Combining Fourier transform infrared spectroscopy (FTIR) with endoscopy, it is expected that noninvasive, rapid detection of colorectal cancer can be performed in vivo in the future. In this study, Fourier transform infrared spectra were collected from 88 endoscopic biopsy colorectal tissue samples (41 colitis and 47 cancers). A new method, viz., entropy weight local-hyperplane k-nearest-neighb...

T nearest-neighbor classifier has been shown to be a powerful tool for multiclass classification. We explore both theoretical properties and empirical behavior of a variant method, in which the nearest-neighbor rule is applied to a reduced set of prototypes. This set is selected a priori by fixing its cardinality and minimizing the empirical misclassification cost. In this way we alleviate the ...

Stewart et al. have shown that flow invariant subspaces for coupled networks are equivalent to a combinatorial notion of a balanced coloring. Wang and Golubitsky have classified all balanced two colorings of planar lattices with either nearest neighbor (NN) or both nearest neighbor and next nearest neighbor coupling (NNN). This classification gives a rich set of patterns and shows the existence...

The nearest neighbor classifier is a powerful, straightforward, and very popular approach to solving many classification problems. It also enables users to easily incorporate weights of training instances into its model, allowing users to highlight more promising examples. Instance weighting schemes proposed to date were based either on attribute values or external knowledge. In this paper, we ...

The realization that entanglement can affect macroscopic properties of bulk solid-state systems is a challenge in physics and Chemistry. Theoretical physicists often are considered the entanglement between nearest-neighbor (NN) spins and tried to find its characterizations in terms of macroscopic thermodynamics observables as magnetization and specific heat. Here, we focus on the entanglement b...