Buscar recursos académicos

"Fault localization is a practical research topic that helps developers identify code locations that might cause bugs in a program. Most existing fault localization techniques are designed for imperative programs (e.g., ...

A new mechanism for strong Anderson localization of photons in carefully prepared disordered dielectric superlattices with an everywhere real positive dielectric constant is described. In three dimensions, two photon mob...

We propose a technique for producing `visual explanations' for decisions from a large class of Convolutional Neural Network (CNN)-based models, making them more transparent. Our approach - Gradient-weighted Class Activat...

In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network (CNN) to have remarkable localization ability despite being trained...

As geography studies the social construction of space is no any longer possible to mantain a “sustantive” interpretation of space. The evolution of the social thoutht and social theory have rescued space as a subject o...

We propose an algorithm for the simultaneous position and clock tracking of a wireless mobile node by a set of reference nodes. Based on a protocol similar to that of two-way ranging, our algorithm efficiently estimates ...

We introduce a method for optically imaging intracellular proteins at nanometer spatial resolution. Numerous sparse subsets of photoactivatable fluorescent protein molecules were activated, localized (to approximately 2 ...

En este trabajo se estudia como la política fiscal y los costos de transporte determinan la distribución geográfica de los trabajadores y las familias. Se utiliza un modelo simple de dos regiones con costos de transpo...

Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP). It allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniqu...

This paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enoug...

In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with...

Abstract The optical constants of amorphous Ge are determined for the photon energies from 0.08 to 1.6 eV. From 0.08 to 0.5 eV, the absorption is due to k ‐conserving transitions of holes between the valence bands as i...

The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framew...