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...

Pigeons were tested in a search task on the surface of a monitor on which their responses were registered by a touch-sensitive device. A graphic landmark array was presented consisting of a square outline (the frame) and a colored "landmark." The unmarked goal, pecks at which produced reward, was located near the center of one edge of the frame, and the landmark was near it. The entire array wa...

In exposing facial fractures for reduction and fixation with coronal, subciliary, subtarsal, and upper buccal sulcus approaches, the supraorbital and infraorbital nerves are susceptible to injury. The location of the supraorbital and infraorbital nerves can be predicted by palpating for the supraorbital notch. Significant edema as seen with facial fractures can make these prominent bony landmar...

This paper presents a novel landmark generating method for robust multi-robot localization and tracking. Although the conventional approaches are able to generate a number of landmarks, they often tend to misjudge or ignore some landmark in particular environment. Analyzing those methods, we suggest the new landmark that is referred to here as Rotating Triangles (RT) landmark. RT landmark imple...