The performance of edge detection often relies on its ability to correctly determine the dissimilarities of connected pixels. For grayscale images, the dissimilarity of two pixels is estimated by a scalar difference of their intensities and for color images, this is done by using the vector difference (color distance) of the three-color components. The Euclidean distance in the RGB color space ...

This paper proposes an adaptive Mahalanobis distance for face retrieval. The distance is derived from a posterior distribution of observation errors in features categorized by con dence of face images. Since the distance is calculated considering error variances of each dimension according to the con dence, it can re ect error distribution of each matching more precisely than a standard Mahalan...

Rousseeuw’s minimum covariance determinant (MCD) method is a highly robust estimator of multivariate mean and covariance. In practice, the MCD covariance estimator may be singular. However, a nonsingular covariance estimator is required to calculate the Mahalanobis distance. In order to fix this singular problem, we propose an improved version of the MCD estimator, which is a combination of the...

The scaling parameter α helps maintain a balance between supervised and unsupervised learning in semi-supervised Fuzzy c-Means (ssFCM). In this study, we investigated the effects of different α values, 0.1, 0.5, 1 and 10 in Pedrycz and Waletsky’s ssFCM with various amounts of labelled data, 10%, 20%, 30%, 40%, 50% and 60% and three distance metrics, Euclidean, Mahalanobis and kernel-based on th...

To predict key variables of complicated batch processes, the long short-term memory (LSTM) soft sensor is developed to deal with both data nonlinearity and dynamics. extract proper historical samples implement real-time modeling scheme model updating strategy, just-in-time learning (JITL) algorithm widely used at selection stage LSTM sensor. However, multiphase issue processes are not considere...