Function Regression by using Fuzzy Hough Transforms.

DNA Microarray Spot Detection Using Hough Transforms

Genetic fingerprinting using DNA microarrays has shown significant promise in rapidly detecting dangerous microorganisms. Though primarily a genetic and bio-chemical technology, one stage of the detection process records an image of the genetic signature. This image contains a variety of illuminated spots which indicate the type of microorganism by their location and intensity. Analyzing these ...

Representing Directions for Hough Transforms

Many algorithms in computer vision operate with directions, i. e. with representations of 3D-points by ignoring their distance to the origin. Even though minimal parametrizations of directions may contain singularities, they can enhance convergence in optimization algorithms and are required e. g. for accumulator spaces in Hough transforms. There are numerous possibilities for parameterizing di...

A framework for junction detection using local Hough transforms

A novel method of junction detection in images is investigated. Junctions are modeled using locally applied Hough transforms. Two types of the Hough transform are proposed: (a) 1D transforms to characterize orientations of the junction segments and (b) 2D transforms to additionally estimate lengths of the segments. For any location of the circular window, the best-fit junction can be found and ...

Generalized Hough Transforms with Flexible Templates

Quantum Energy Regression using Scattering Transforms

We present a novel approach to the regression of quantum mechanical energies based on a scattering transform of an intermediate electron density representation. A scattering transform is a deep convolution network computed with a cascade of multiscale wavelet transforms. It possesses appropriate invariant and stability properties for quantum energy regression. This new framework removes fundame...