Listar por tema "Neural networks"
Mostrando ítems 21-40 de 73
-
Deep Endoscopic Visual Measurements
(2019)Robotic endoscopic systems offer a minimally invasive approach to the examination of internal body structures, and their application is rapidly extending to cover the increasing needs for accurate therapeutic interventions. ... -
Deep learning and change detection for fall recognition
(2019)Early 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 daily-life activities ... -
Deep View2View Mapping for View-Invariant Lipreading
(2019)Recently, visual-only and audio-visual speech recognition have made significant progress thanks to deep-learning based, trainable visual front-ends (VFEs), with most research focusing on frontal or near-frontal face videos. ... -
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification
(2018)This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only ... -
Detection of malignant melanomas in dermoscopic images using convolutional neural network with transfer learning
(2017)In this work, we report the use of convolutional neural networks for the detection of malignant melanomas against nevus skin lesions in a dataset of dermoscopic images of the same magnification. The technique of transfer ... -
Efficient Learning Rate Adaptation for Convolutional Neural Network Training
(2019)Convolutional Neural Networks (CNNs) have been established as substantial supervised methods for classification problems in many research fields. However, a large number of parameters have to be tuned to achieve high ... -
Enhanced short-term load forecasting using artificial neural networks
(2021)The modernization and optimization of current power systems are the objectives of research and development in the energy sector, which is motivated by the ever-increasing electricity demands. The goal of such research and ... -
Estimation of models for cumulative infiltration of soil using machine learning methods
(2021)Knowledge of cumulative infiltration of soil is necessary for irrigation, surface flow, groundwater recharge and many other hydrological processes. In the present study, the Support Vector Machine (SVM), artificial neural ... -
Exploring an ensemble of methods that combines fuzzy cognitive maps and neural networks in solving the time series prediction problem of gas consumption in Greece
(2019)This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim ... -
Fingerspelled alphabet sign recognition in upper-body videos
(2019)Fingerspelling is a crucial part of sign-based communication, however its recognition remains a challenging and mostly overlooked computer vision problem. To address it, this paper presents a system that recognizes the 24 ... -
Fire resistance prediction of slim-floor asymmetric steel beams using single hidden layer ANN models that employ multiple activation functions
(2022)In this paper a mathematical model for the prediction of the fire resistance of slim-floor steel beams based on an Artificial Neural Network modeling procedure is presented. The artificial neural network models are trained ... -
Fusing Handcrafted and Contextual Features for Human Activity Recognition
(2019)In this paper we present an approach for the recognition of human activity that combines handcrafted features from 3D skeletal data and contextual features learnt by a trained deep Convolutional Neural Network (CNN). Our ... -
Fusion using neural networks for intoxication identification
(2018)Fusion of dissimilar features by means of neural networks is demonstrated in this work aiming at improving the performance of these features for drunk person identification. The features are coming from the thermal images ... -
A High-Performance Neuron for Artificial Neural Network based on Izhikevich model
(2019)Neuromorphic circuits have gained a lot of interest through the last decades since they may be deployed in a large spectrum of scientific research. In this paper a hardware realization of a single neuron targeting Field ... -
A Hybrid Approach to Hand Detection and Type Classification in Upper-Body Videos
(2019)Detection of hands in videos and their classification into left and right types are crucial in various human-computer interaction and data mining systems. A variety of effective deep learning methods have been proposed for ... -
Hybrid model for water demand prediction based on fuzzy cognitive maps and artificial neural networks
(2016)In this study, we propose a new hybrid approach for time series prediction based on the efficient capabilities of fuzzy cognitive maps (FCMs) with structure optimization algorithms and artificial neural networks (ANNs). ... -
Hyper-parameters Tuning of Artificial Neural Networks: An Application in the Field of Recommender Systems
(2022)In this work, we carry out the hyper-parameters tuning of a Machine Learning (ML) Recommender Systems (RS) which utilizes an Artificial Neural Network (ANN), called CATA++. We have performed tuning of the activation function, ... -
Implementing fuzzy cognitive maps with neural networks for natural gas prediction
(2018)The goal of this research study is to test the hardiness of a novel hybrid computational intelligence model in day-ahead natural gas demand prediction. The proposed model combines an evolutionary learned FCM method with a ... -
Improving the performance of convolutional neural network for skin image classification using the response of image analysis filters
(2019)In this work, we focus in the analysis of dermoscopy images using convolutional neural networks (CNNs). More specifically, we investigate the value of augmenting CNN inputs with the response of mid-level computer vision ... -
Indirect adaptive neural control for precalcination in cement plants
(2002)Control of the precalcination degree in the precalciner of cement plants is a problem of great importance due to its effect to the quality of the clinker, the consumed energy and the byproducts of the whole cement pyroprocess. ...