A knowledge-based approach to the detection, tracking and classification of target formations in infrared image sequences

2003 ◽  
Author(s):  
J.F. Bronskill ◽  
J.S.A. Hepburn ◽  
W.K. Au
Keyword(s):  
Infrared Image ◽  
Image Sequences ◽  
Knowledge Based

Detection And Classification Of Target Formations In Infrared Image Sequences

1989 ◽  
Author(s):  
John F. Bronskill ◽  
John S. A. Hepburn ◽  
Wing K. Au
Keyword(s):  
Infrared Image ◽  
Image Sequences

A Method for Classification of Transient Events in EEG Recordings: Application to Epilepsy Diagnosis

2006 ◽  
Vol 45 (06) ◽  
pp. 610-621 ◽  
Author(s):  
A. T. Tzallas ◽  
P. S. Karvelis ◽  
C. D. Katsis ◽  
S. Giannopoulos ◽  
S. Konitsiotis ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Epileptic Activity ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Epilepsy Diagnosis ◽  
Transient Events ◽  
Artificial Neural ◽  
Eeg Recordings

Summary Objectives: The aim of the paper is to analyze transient events in inter-ictal EEG recordings, and classify epileptic activity into focal or generalized epilepsy using an automated method. Methods: A two-stage approach is proposed. In the first stage the observed transient events of a single channel are classified into four categories: epileptic spike (ES), muscle activity (EMG), eye blinking activity (EOG), and sharp alpha activity (SAA). The process is based on an artificial neural network. Different artificial neural network architectures have been tried and the network having the lowest error has been selected using the hold out approach. In the second stage a knowledge-based system is used to produce diagnosis for focal or generalized epileptic activity. Results: The classification of transient events reported high overall accuracy (84.48%), while the knowledge-based system for epilepsy diagnosis correctly classified nine out of ten cases. Conclusions: The proposed method is advantageous since it effectively detects and classifies the undesirable activity into appropriate categories and produces a final outcome related to the existence of epilepsy.

scholarly journals ON A KNOWLEDGE-BASED APPROACH TO THE CLASSIFICATION OF MOBILE LASER SCANNING POINT CLOUDS

2018 ◽  
Vol XLII-4 ◽  
pp. 343-349 ◽  
Author(s):  
M. Lemmens
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Decision Rules ◽  
Point Clouds ◽  
Bench Mark ◽  
Automated Classification ◽  
Initial Experiment ◽  
Data Set ◽  
Knowledge Based

<p><strong>Abstract.</strong> A knowledge-based system exploits the knowledge, which a human expert uses for completing a complex task, through a database containing decision rules, and an inference engine. Already in the early nineties knowledge-based systems have been proposed for automated image classification. Lack of success faded out initial interest and enthusiasm, the same fate neural networks struck at that time. Today the latter enjoy a steady revival. This paper aims at demonstrating that a knowledge-based approach to automated classification of mobile laser scanning point clouds has promising prospects. An initial experiment exploiting only two features, height and reflectance value, resulted in an overall accuracy of 79<span class="thinspace"></span>% for the Paris-rue-Madame point cloud bench mark data set.</p>

scholarly journals MASONRY IN PARALLEL. A KNOWLEDGE BASED STRATEGY POST CENTRAL ITALY EARTHQUAKE 2016

2020 ◽  
Vol XLIV-M-1-2020 ◽  
pp. 3-9
Author(s):  
C. Braucher ◽  
E. Currà
Keyword(s):  
Central Italy ◽  
Field Research ◽  
Masonry Buildings ◽  
Knowledge Based ◽  
Central Italy Earthquake ◽  
Survey Form ◽  
Umbria Region ◽  
Post Traumatic ◽  
New Form

Abstract. This research aims to propose a classification of masonry typologies in Central Italy after the earthquakes that in 2016 involved about 120 municipalities. This territory, since several decades, presents high fragility features due to the depopulation process that increase the vulnerability and risk degree. This condition affects even the maintenance practices of traditional buildings by the inhabitants and the extraordinary post-traumatic situation acts as an accelerating factor of the abandonment. In this article we will explain deeply the first part of the research, focusing in particular on methods and tools that were defined and used to carry out this study. The research highlights the need of a specific comparative tool for masonry facades classification. This was elaborated through the comparison of existed bibliography as the EMS-98, the Aedes schedules and the local classification by Umbria Region and the De Meo book. The result then is the production of another synoptic map that would simplifies the correlation between different approaches to classification and the censed facades. Moreover, it was elaborated a second synoptic map moving from the analyses of many survey forms already discuss in literature. The result of this comparison is a new survey form to carry out the field research on vernacular masonry buildings. This new form focuses on the characteristics of the buildings that the research aims to study in Central Italy. The two tools that are illustrate in the following paper were applied on one hundred survey of masonry buildings carried out during August 2018. The last part of this paper proposes a statistical analysis of the results of the field research.

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