Academic Articles & Research Papers

Computer Vision

From the Publisher: Computer Vision presents the necessary theory and techniques for students and practitioners who will work in fields where significant information must be extracted automatically from images. It will be a useful resource...

ALGORITMO PARA O RECONHECIMENTO DE CARACTERES MANUSCRITOS

The handwritten character recognition in digital images is an important and challenging area of study in Computer Vision, with several possibilities for applications to facilitate the daily work of the people. This paper presents an alg...

Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks

One of the essential abilities in animals is to detect novelties within their environment. From the computational point of view, novelty detection consists of finding data that are different in some aspect to the known data. In robotics, re...

Wasserstein Generative Adversarial Network Based De-Blurring Using Perceptual Similarity

The de-blurring of blurred images is one of the most important image processing methods and it can be used for the preprocessing step in many multimedia and computer vision applications. Recently, de-blurring methods have been performed by ...

Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics

Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control appli...

Neural networks in geophysical applications

Abstract Neural networks are increasingly popular in geophysics. Because they are universal approximators, these tools can approximate any continuous function with an arbitrary precision. Hence, they may yield important contributions to fin...

An Overview of Neural Network

Neural networks represent a brain metaphor for information processing. These models are biologically inspired rather than an exact replica of how the brain actually functions. Neural networks have been shown to be very promising systems in ...

Building neural networks

Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...

Applying Neural Networks: A Practical Guide

Techniques for building neural networks: introduction what are neural networks? how does neural computing differ from traditional programming? how are neural networks built? how do neural networks learn? what do I need to build an MLP? the ...

Artificial neural network and wavelet neural network approaches for modelling of a solar air heater

Introduction Neural networks in remote sensing

Abstract. Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that ...

Neural Networks: Methodology and Applications

Modeling of Self-Aligned Selector Based on Ultra-Thin Metal Oxide for Resistive Random-Access Memory (RRAM) Crossbar Arrays

Resistive random-access memory (RRAM) is a crucial element for next-generation large-scale memory arrays, analogue neuromorphic computing and energy-efficient System-on-Chip applications. For these applications, RRAM elements are arranged i...

Neural networks at work

The benefits of neural networks and the types of application for which they are suited are outlined. Four representative applications are described in enough detail to show how they work. They are character recognition, function estimation,...

Research on Kalman Filter Fusion Navigation Algorithm Assisted by CNN-LSTM Neural Network

In response to the challenge of single navigation methods failing to meet the high precision requirements for unmanned aerial vehicle (UAV) navigation in complex environments, a novel algorithm that integrates Global Navigation Satellite Sy...

Shear banding and flow instabilities in wormlike micelles: Modelling and mechanisms – A review

Worm-like micelles (WLMs) are dynamic, self-assembling supramolecular structures that exhibit complex viscoelastic behaviour due to their ability to undergo reversible scission, fusion, branching, and sequence rearrangement. This review pro...

Neural Networks in Chemistry

Abstract The capabilities of the human brain have always fascinated scientists and led them to investigate its inner workings. Over the past 50 years a number of models have been developed which have attempted to replicate the brain's vario...

Neural Networks for Chemists: An Introduction

From the Publisher: This book gives chemists insight into the much discussed and often not fully understood concept of neural networks. The authors pinpoint the five most widely used neural networks and learning strategies, illustrating th...

Neural Networks in Materials Science.

There are difficult problems in materials science where the general concepts might be understood but which are not as yet amenable to scientific treatment. We are at the same time told that good engineering has the responsibility to reach o...

Neural networks for signal processing

This collection of essays explores neural networks applications in signal and image processing, function and estimation, robotics and control, associative memories, and electrical and optical networks. Intended as a companion to Neural Netw...