conclusions the us-guided method for cvc placement was superior to the traditional landmark method in terms of access time, number of attempts, success rate, and fewer complications. objectives this study aimed to compare the traditional landmark method vs. us-guided method of cvc placement in terms of complications and success rate. patients and methods in this randomized controlled trial, pat...

Two experiments investigated how people develop different landmark knowledge at decision points. Participants learned a route in a virtual city once or five times. One distinctive landmark was placed at each intersection of the route. At test, participants were released at each intersection according to the learning order and were required to determine the turning direction. At each intersectio...

One area of voice research that has historically been understudied is the interaction between voice pathology and acoustic aspects of the speech signal that affect intelligibility. Landmark-based software tools are particularly suited to fast, automatic analysis of small, non-lexical differences in the acoustic signal reflecting the production of speech. We are building a tool set that provides...

This paper presents a novel fuzzy-symbolic approach for the recognition of two-dimensional shapes. The proposed method represents a binary shape using symbolic (multi interval valued) features. The representation scheme is based on the landmark points (dominant points) of the shape and the concept of fuzzy equilateral triangle membership function. A similarity measure to estimate the degree of ...

Maximally Collapsing Metric Learning is a recently proposed algorithm to estimate a metric matrix from labelled data. The purpose of this work is to extend this approach by considering a set of landmark points which can in principle reduce the cost per iteration in one order of magnitude. The proposal is in fact a generalized version of the original algorithm that can be applied to larger amoun...

An automatic method for the selection of subsets of images, both modern and historic, out of a set of landmark large images collected from the Internet is presented in this paper. This selection depends on the extraction of dominant features using Gabor filtering. Features are selected carefully from a preliminary image set and fed into a neural network as a training data. The method collects a...

The Gaussian distribution is the basis for many methods used in the statistical analysis of shape. One such method is principal component analysis, which has proven to be a powerful technique for describing the geometric variability of a population of objects. The Gaussian framework is well understood when the data being studied are elements of a Euclidean vector space. This is the case for geo...

In the visual fashion clothing analysis, many researchers are attracted with success of deep learning concepts. this work, we introduce a multi-staged feature-attentive network to attain category classification and attribute prediction. The proposed in work brings out landmark-independent structure, whereas existing landmark-dependent structures take up lot manpower for landmark annotation also...