toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
  Records Links
Author Rangnekar,Aneesha; Mulhollan,Zachary; Vodacek,Anthony; Hoffman,Matthew; Sappa,Angel D.; Yu,Jun et al. pdf  openurl
  Title (down) Semi-Supervised Hyperspectral Object Detection Challenge Results-PBVS 2022. Type Conference Article
  Year 2022 Publication Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE  
  Volume 2022-June Issue Pages 389-397  
  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 cidis @ cidis @ Serial 176  
Permanent link to this record
 

 
Author Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias pdf  openurl
  Title (down) Scene representations for autonomous driving: an approach based on polygonal primitives Type Conference Article
  Year 2015 Publication Iberian Robotics Conference (ROBOT 2015), Lisbon, Portugal, 2015 Abbreviated Journal  
  Volume 417 Issue Pages 503-515  
  Keywords Scene reconstruction, Point cloud, Autonomous vehicles  
  Abstract In this paper, we present a novel methodology to compute a 3D scene representation. The algorithm uses macro scale polygonal primitives to model the scene. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Results show that the approach is capable of producing accurate descriptions of the scene. In addition, the algorithm is very efficient when compared to other techniques.  
  Address  
  Corporate Author Thesis  
  Publisher Springer International Publishing Switzerland 2016 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 Second Iberian Robotics Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 45  
Permanent link to this record
 

 
Author Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla pdf  openurl
  Title (down) RWE patterns extraction for on-line human action recognition through window-based analysis of invariant moments Type Conference Article
  Year 2012 Publication 5th Workshop in applied Robotics and Automation (RoboControl) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Human action recognition, Relative Wavelet Energy, Window-based temporal analysis.  
  Abstract This paper presents a method for on-line human action recognition on video sequences. An analysis based on Mahalanobis distance is performed to identify the “idle” state, which defines the beginning and end of the person movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments.  
  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 cidis @ cidis @ Serial 23  
Permanent link to this record
 

 
Author Angel Morera; Angel Sánchez; Angel D. Sappa; José F. Vélez pdf  openurl
  Title (down) Robust Detection of Outdoor Urban Advertising Panels in Static Images. Type Conference Article
  Year 2019 Publication 17th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2019); Ávila, España. Communications in Computer and Information Science Abbreviated Journal  
  Volume 1047 Issue Pages 246-256  
  Keywords  
  Abstract One interesting publicity application for Smart City environments is recognizing brand information contained in urban advertising

panels. For such a purpose, a previous stage is to accurately detect and

locate the position of these panels in images. This work presents an effective solution to this problem using a Single Shot Detector (SSD) based

on a deep neural network architecture that minimizes the number of

false detections under multiple variable conditions regarding the panels and the scene. Achieved experimental results using the Intersection

over Union (IoU) accuracy metric make this proposal applicable in real

complex urban images.
 
  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 gtsi @ user @ Serial 107  
Permanent link to this record
Select All    Deselect All
 |   | 
Details

Save Citations:
Export Records: