Search results for "Process"
showing 10 items of 22310 documents
A Feed-Forward Neural Network for Robust Segmentation of Color Images
1999
A novel approach for segmentation of color images is proposed. The approach is based on a feed-forward neural network that learns to recognize the hue range of meaningful objects. Experimental results showed that the proposed method is effective and robust even in presence of changing environmental conditions. The described technique has been tested in the framework of the Robot Soccer World Cup Initiative (RoboCup). The approach is fully general and it may be successfully employed in any intermediate level image-processing task, where the color is a meaningful descriptor.
An Encrypted Traffic Classification Framework Based on Convolutional Neural Networks and Stacked Autoencoders
2020
In recent years, deep learning-based encrypted traffic classification has proven to be effective; especially, using neural networks to extract features from raw traffic to classify encrypted traffic. However, most of the neural networks need a fixed-sized input, so that the raw traffic need to be trimmed. This will cause the loss of some information; for example, we do not know the number of packets in a session. To solve these problems, a framework, which implements both a convolutional neural network (CNN) and a stacked autoencoder (SAE), is proposed in this paper. This framework uses a CNN to extract high-level features from raw network traffic and uses an SAE to encode the 26 statistica…
A Neural Architecture for 3D Segmentation
2003
An original neural scheme for segmentation of range data is presented, which is part of a more general 3D vision system for robotic applications. The entire process relies on a neural architecture aimed to perform first order image irradiance analysis, that is local estimation of magnitude and orientation of the image irradiance gradient.
A Memetic-Neural Approach to Discover Resources in P2P Networks
2008
This chapter proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing in training of the neural network. The neural network, which is a multi-layer perceptron neural network, allows the P2P nodes to efficiently locate resources desired by the user. The necessity of testing the network in various working conditions, aiming to obtain a robust neural network, introduces noise in the objective function. The AGLMA is a memetic algorithm which employs two local search algorithms adaptively activated by an evolutionary framework. These local searchers, having different fe…
Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators
2021
One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…
The mediating role of behavioural automaticity and intention on past to future bootcamp attendance
2023
Objective The aim of the current study was to test whether behavioural automaticity and intention mediated the effects of past behaviour on a particular type of vigorous physical exercise: bootcamp attendance. Methods A community sample (N = 69) who had previously attended a bootcamp class was recruited from Queensland, Australia. Participants were asked to complete measures of their previous bootcamp attendance, behavioural automaticity, and intention to attend bootcamps (Time 1). One month later (Time 2), participants were asked to report their bootcamp attendance and behavioural automaticity in the previous month. Data were fitted to a Partial Least Squares-SEM model. Results Past behavi…
Dynamiques urbaines en Asie du Sud-Est
2014
L’urbanisation mondiale est un phenomene irrepressible. Les aires urbaines, accueillent desormais plus d’habitants que les campagnes. L’acceleration de la croissance urbaine, fortement correlee a la mondialisation, a l’expansion de l’economie de marche et des technologies modernes, se marque en particulier par l’emergence de grandes metropoles, de « megacites ». Le concept meme de ville est remis en question par l’explosion demographique et l’etalement urbain. Les villes-centre sont desormais...
Panel Discussion on Trends in Optical and Radio Data Analysis
1985
Albrecht: What I want to do is to give a brief five-minute introduction to the subject, justifying the title which puts optical and radio astronomy in one and the same category, which I believe it is, as far as data analysis is concerned, and then I will ask the panel members to give us two-minute statements of their opinions on the subject and then I would like to ask the audience to fire questions at us.
Eco-extraction and encapsulation of carotenoid and anthocyanin pigments from tropical plants
2018
This thesis deals with extraction processes using assistance technologies or green solvents and encapsulation systems of natural pigments in order to exploit and apply them in the food, cosmetic and pharmaceutical industries. In this goal, microwave-assisted extraction (MAE), ultrasonic-assisted extraction (UAE) and Ionic liquids (IL) were evaluated for the extraction of carotenoids and anthocyanins from Vietnamese plants. The results obtained show that the MAE was always a rapid and helpful system for all types of extraction tested whereas ultrasounds were particularly efficient when pigments are present on the surface of plant tissues. However, UAE was also improving results compared to c…
3D Matrix-Based Visualization System of Association Rules
2017
With the growing number of mining datasets, it becomes increasingly difficult to explore interesting rules because of the large number of resultant and its nature complexity. Studies on human perception and intuition show that graphical representation could be a better illustration of how to seek information from the data using the capabilities of human visual system. In this work, we present and implement a 3D matrix-based approach visualization system of association rules. The main visual representation applies the extended matrix-based approach with rule-to-items mapping to general transaction data set. A novel method merging rules and assigning weight is proposed in order to reduce the …