Listar por tema "Neural networks"
Mostrando ítems 1-20 de 73
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Aeroacoustics and Artificial Neural Network Modeling of Airborne Acoustic Emissions During High Kinetic Energy Thermal Spraying
(2019)This work describes an online, non-destructive monitoring technology for thermal spray coating processes based on the airborne acoustic emissions (AAE) in the booth. First, numerical simulations were carried out to probe ... -
An ANN approach on the optimization of the cutting parameters during CNC plasma-arc cutting
(2010)The objective of the present study is to develop an Artificial Neural Network (ANN) in order to predict the bevel angle (response variable) during CNC plasma-arc cutting of St37 mild steel plates. The four (4) input ... -
Applied Artificial Neural Networks and Genetic Algorithms in Simulation Strategy for Trajectory in Collaborative Robotic
(2021)This work proposes a solution for collaborative robotics, presenting some precautions with this new perspective of robotics and norm, trajectory planning and observed singularities. Also, it compares techniques for solving ... -
Applying Long Short-Term Memory Networks for natural gas demand prediction
(2019)Long Short-Term Memory (LSTM) algorithm encloses the characteristics of the advanced recurrent neural network methods and is used in this research study to forecast the natural gas demand in Greece in the short-term. LSTM ... -
Applying unsupervised and supervised machine learning methodologies in social media textual traffic data
(2019)Traffic increasingly shapes the trajectory of city growth and impacts on the climate change in modern cities. Traffic patterns’ monitoring can provide with innovative practices in understanding city traffic dynamics, ... -
Arm Gesture Recognition using a Convolutional Neural Network
(2018)In this paper we present an approach towards arm gesture recognition that uses a Convolutional Neural Network (CNN), which is trained on Discrete Fourier Transform (DFT) images that result from raw sensor readings. More ... -
An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy
(2017)Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with ... -
Artificial Neural Networks and Principal Components Analysis for Detection of Idiopathic Pulmonary Fibrosis in Microscopy Images
(2013)In this study we present a computer assisted image identification and recognition tool that aims to help the diagnosis of idiopathic pulmonary fibrosis in microscopy images. To this end, we use principal components analysis ... -
Artificial neural networks modeling of surface finish in electro-discharge machining of tool steels
(2006)Electro-Discharge machining (EDM) is a thermal process with a complex metal removal mechanism that involves the formation of a plasma channel between the tool and the workpiece electrodes and the melting and evaporation ... -
Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks
(2017)One of the most important policy reforms for the European Union (EU) agriculture was the implementation of the Agenda 2000, which establishes a new framework for subsidies management, decoupled from both crop and animal ... -
Assessing image analysis filters as augmented input to convolutional neural networks for image classification
(2018)Convolutional Neural Networks (CNNs) have been proven very effective in image classification and object recognition tasks, often exceeding the performance of traditional image analysis techniques. However, training a CNN ... -
Change detection and convolution neural networks for fall recognition
(2020)Accurate fall detection is a crucial research challenge since the time delay from fall to first aid is a key factor that determines the consequences of a fall. Wearable sensors allow a reliable way for motion tracking, ... -
A Comparison of Feature Selection Techniques for Neural Network Based Load Forecasting
(2019)The performance of neural networks in load forecasting tasks is highly influenced by the selection of the inputs. This selection is either problem specific or is relied on the literature. The scope of the present study is ... -
The contribution of ANN's simple perceptron pattern to inequalities measurement in Regional Science
(2013)The present paper presents a synthetic approach to the XOR operation structure combining the cognitive matter of different fields of scientific study in order to elect further utility of this operation for the inequalities ... -
Convolutional neural networks for pose recognition in binary omni-directional images
(2016)In this work, we present a methodology for pose classification of silhouettes using convolutional neural networks. The training set consists exclusively from the synthetic images that are generated from three-dimensional ... -
Convolutional neural networks for toxic comment classification
(2018)Flood of information is produced in a daily basis through the global internet usage arising from the online interactive communications among users. While this situation contributes significantly to the quality of human ... -
Crowd Sourcing as an Improvement of N-Grams Text Document Classification Algorithm
(2020)A common task in a world of natural language processing is text classification useful for e.g.spam filters, documents sorting, science articles classification or plagiarism detection. This can still be done best and most ... -
Daily multivariate forecasting of water demand in a touristic island with the use of artificial neural network and adaptive neuro-fuzzy inference system
(2016)Water demand forecast has emerged as an imperative component of intelligent Internet and Communication Technologies based methodologies of water management. The need of increased time resolution of forecast in order to ... -
Day-ahead natural gas demand forecasting in hourly resolution
(2021)Natural Gas (NG) demand forecasting is a research topic that starts to gather the attention of scholars, research institutions, utilities, retailers and other interested parties. Accurate predictions of future needs for ... -
Deep affordance-grounded sensorimotor object recognition
(2017)It is well-established by cognitive neuroscience that human perception of objects constitutes a complex process, where object appearance information is combined with evidence about the so-called object “affordances”, namely ...