This study presents two sets of translation invariant wavelet transforms for coding an arbitrarily shaped image. Each set can be viewed as a shape-adaptive discrete wavelet transform (SA-DWT) with the property of translation invariance. The proposed transform schemes have the following merits: (1) they are translation invariant, (2) no sharp transition appears at the edges of the image, (3) the...

Abstract. The Short Boredom Proneness Scale (SBPS) has recently been developed. Using a standard confirmatory factor analysis, we report on the structural validation of French SBPS, which provided support for original construct. A network analysis ( n = 490) revealed structure relationships between SBPS and two facets Curiosity Exploration Inventory-II (CEI-II). positive connections boredom cur...

Four experiments were conducted to study the nature of visual translation invariance in humans. In all the experiments, subjects were trained to discriminate between a previously unknown target and two non-target distractors presented at a fixed retinal location to one side of the fixation point. In a subsequent test phase, this performance was compared with the performance when the patterns we...

Biederman and Cooper (1991a) showed that the presentation of a briefly presented image of an object at one position in the visual field facilitated its identification, as assessed by naming speed and accuracy, several minutes later. The facilitation was unaffected by a translation or a reflection of the stimulus. A component of this priming was visual rather than basic-level conceptual or lexic...

In this paper we study the global regularity for solution to Dirichlet problem of equation minimal graphs over a convex domain in hyperbolic spaces. We find that depends only on convexity but independent its smoothness. Basing invariance under translation and rotation transforms, construct super-solution problem, by which prove optimal accurate problem.

Humans can recognize objects in a way that is invariant to scale, translation, and clutter. We use invariance theory as a conceptual basis, to computationally model this phenomenon. This theory discusses the role of eccentricity in human visual processing, and is a generalization of feedforward convolutional neural networks (CNNs). Our model explains some key psychophysical observations relatin...

We continue the work started in [Å-I], and prove the invariance and universality in the class of finite type invariants of the object defined and motivated there, namely the Århus integral of rational homology 3-spheres. Our main tool in proving invariance is a translation scheme that translates statements in multi-variable calculus (Gaussian integration, integration by parts, etc.) to statemen...

A new algorithm for learning invariance manifolds is introduced that allows a neuron to learn a non-linear transfer function to extract invariant or rather slowly varying features from a vectorial input sequence. This is generalized to a group of neurons, referred to as a Gibson-clique, to learn slowly varying features that are uncorrelated. Since the transfer functions are non-linear, this tec...

The general formalisms of the $q$-dual statistics, Boltzmann-Gibbs and three versions Tsallis statistics known as Tsallis-1, Tsallis-2, Tsallis-3 have been considered in canonical ensemble. We rigorously proved that probability distribution Tsallis-1 is invariant under uniform energy spectrum translation at a fixed temperature. This invariance demonstrates formalism consistent with fundamentals...