toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
  Records Links
Author Miguel Realpe; Boris X. Vintimilla; L. Vlacic pdf  openurl
  Title Towards Fault Tolerant Perception for autonomous vehicles: Local Fusion. Type Conference Article
  Year 2015 Publication IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), Siem Reap, 2015. Abbreviated Journal  
  Volume Issue Pages 253-258  
  Keywords  
  Abstract Many robust sensor fusion strategies have been developed in order to reliably detect the surrounding environments of an autonomous vehicle. However, in real situations there is always the possibility that sensors or other components may fail. Thus, internal modules and sensors need to be monitored to ensure their proper function. This paper introduces a general view of a perception architecture designed to detect and classify obstacles in an autonomous vehicle's environment using a fault tolerant framework, whereas elaborates the object detection and local fusion modules proposed in order to achieve the modularity and real-time process required by the system.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 37  
Permanent link to this record
 

 
Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic pdf  url
openurl 
  Title Sensor Fault Detection and Diagnosis for autonomous vehicles Type Conference Article
  Year 2015 Publication 2nd International Conference on Mechatronics, Automation and Manufacturing (ICMAM 2015), International Conference on, Singapur, 2015 Abbreviated Journal  
  Volume 30 Issue MATEC Web of Conferences Pages 1-6  
  Keywords  
  Abstract In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor.  
  Address  
  Corporate Author Thesis  
  Publisher EDP Sciences Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 42  
Permanent link to this record
 

 
Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic pdf  openurl
  Title Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles Type Journal Article
  Year 2016 Publication Journal of Automation and Control Engineering (JOACE) Abbreviated Journal  
  Volume Vol. 4 Issue Pages pp. 430-436  
  Keywords Fault Tolerance, Data Fusion, Multi-sensor Fusion, Autonomous Vehicles, Perception System  
  Abstract Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 51  
Permanent link to this record
 

 
Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic pdf  openurl
  Title A Fault Tolerant Perception system for autonomous vehicles Type Conference Article
  Year 2016 Publication 35th Chinese Control Conference (CCC2016), International Conference on, Chengdu Abbreviated Journal  
  Volume Issue Pages 1-6  
  Keywords Fault Tolerant Perception, Sensor Data Fusion, Fault Tolerance, Autonomous Vehicles, Federated Architecture  
  Abstract Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 52  
Permanent link to this record
 

 
Author Sianna Puente; Cindy Madrid; Miguel Realpe; Boris X. Vintimilla pdf  openurl
  Title An Empirical Comparison of DCNN libraries to implement the Vision Module of a Danger Management System Type Conference Article
  Year 2017 Publication 2017 International Conference on Deep Learning Technologies (ICDLT 2017) Abbreviated Journal  
  Volume Part F128535 Issue Pages 60-65  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 56  
Permanent link to this record
 

 
Author Miguel A. Murillo, Julio E. Alvia, & Miguel Realpe url  openurl
  Title Beyond visual and radio line of sight UAVs monitoring system through open software in a simulated environment. Type Conference Article
  Year 2021 Publication The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communications in Computer and Information Science Abbreviated Journal  
  Volume 1388 Issue Pages 629-642  
  Keywords Drone, Open Source, Internet, Web Application, Web Server, SITL, Line of sight, UAV.  
  Abstract The problem of loss of line of sight when operating drones has be-come a reality with adverse effects for professional and amateur drone opera-tors, since it brings technical problems such as loss of data collected by the de-vice in one or more instants of time during the flight and even misunderstand-ings of legal nature when the drone flies over prohibited or private places. This paper describes the implementation of a drone monitoring system using the In-ternet as a long-range communication network in order to avoid the problem of loss of communication between the ground station and the device. For this, a simulated environment is used through an appropriate open software tool. The operation of the system is based on a client that makes requests to a server, the latter in turn communicates with several servers, each of which has a drone connected to it. In the proposed system when a drone is ready to start a flight, its server informs the main server of the system, which in turn gives feedback to the client informing it that the device is ready to carry out the flight; this way customers can send a mission to the device and keep track of its progress in real time on the screen of their web application.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 186  
Permanent link to this record
 

 
Author Luis Jacome-Galarza, Monica Villavicencio-Cabezas, Miguel Realpe-Robalino, Jose Benavides-Maldonado pdf  openurl
  Title Software Engineering and Distributed Computing in image processing intelligent systems: a systematic literature review. Type Conference Article
  Year 2021 Publication 19th LACCEI International Multi-Conference for Engineering, Education, and Technology Abbreviated Journal  
  Volume Issue Pages  
  Keywords processing, software engineering, deep learning, intelligent vision systems, cloud computing.  
  Abstract Deep learning is experiencing an upward technology trend that is revolutionizing intelligent systems in several domains, such as image and speech recognition, machine translation, social network filtering, and the like. By reviewing a total of 80 studies reported from 2016 to 2020, the present article evaluates the application of software engineering to the field

of intelligent image processing systems, it also offers insights about aspects related to distributed computing for this type of systems. Results indicate that several topics of software engineering are mostly applied when academics are involved in developing projects associated to this kind of intelligent systems. The findings provide evidences that Apache Spark is the most

utilized distributed computing framework for image processing. In addition, Tensorflow is a popular framework used to build convolutional neural networks, which are the prevailing deep learning algorithms used in intelligent image processing systems.

Also, among big cloud providers, Amazon Web Services is the preferred computing platform across the industry sectors, followed by Google cloud.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 154  
Permanent link to this record
 

 
Author Emmanuel Moran, Boris Vintimilla & Miguel Realpe openurl 
  Title Towards a Robust Solution for the Supermarket Shelf Audit Problem. Type Conference Article
  Year 2023 Publication Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2023 Abbreviated Journal  
  Volume Issue Pages 912 - 919  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 204  
Permanent link to this record
 

 
Author Pabelco Zambrano, Fernanda Calderon, Héctor Villegas, Jonathan Paillacho, Doménica Pazmiño, Miguel Realpe pdf  isbn
openurl 
  Title UAV Remote Sensing applications and current trends in crop monitoring and diagnostics: A Systematic Literature Review Type Conference Article
  Year 2023 Publication IEEE 13th International Conference on Pattern Recognition Systems (ICPRS) 2023, julio 4-7 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 979-835033337-4 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 214  
Permanent link to this record
 

 
Author Sara Nieto, Evelyn Mejia, Ricardo Villacis, Fernanda Calderon, Hector Villegas, Jonathan Paillacho and Miguel Realpe openurl 
  Title A Practical Study on Banana (Musa spp.) Plant Counting and Coverage Percentage Using Remote Sensing and Deep Learning Type Conference Article
  Year 2023 Publication International Conference on Geospatial Information Sciences, iGISc 2023 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number (up) cidis @ cidis @ Serial 228  
Permanent link to this record
Select All    Deselect All
 |   | 
Details

Save Citations:
Export Records: