Now showing items 1-16 of 16

    • Assessing knee OA severity with CNN attention-based end-to-end architectures 

      Górriz, Marc; Antony, Joseph; McGuinness, Kevin; Giró Nieto, Xavier; O'Connor, Noel (2019)
      Conference lecture
      Open Access
      This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which incorporates trainable attention modules ...
    • Bags of local convolutional features for scalable instance search 

      Mohedano, Eva; Salvador Aguilera, Amaia; McGuinness, Kevin; Marqués Acosta, Fernando; O'Connor, Noel; Giró Nieto, Xavier (Association for Computing Machinery (ACM), 2016)
      Conference lecture
      Open Access
      This work proposes a simple instance retrieval pipeline based on encoding the convolutional features of CNN using the bag of words aggregation scheme (BoW). Assigning each local array of activations in a convolutional layer ...
    • Demonstration of an open source framework for qualitative evaluation of CBIR systems 

      Gomez Duran, Paula; Mohedano, Eva; McGuinness, Kevin; Giró Nieto, Xavier; O'Connor, Noel (Association for Computing Machinery (ACM), 2018)
      Conference lecture
      Open Access
      Evaluating image retrieval systems in a quantitative way, for example by computing measures like mean average precision, allows for objective comparisons with a ground-truth. However, in cases where ground-truth is not ...
    • Exploring EEG for object detection and retrieval 

      Mohedano Robles, Eva; Salvador Aguilera, Amaia; Porta, Sergi; Giró Nieto, Xavier; Healy, Graham; McGuinness, Kevin; O'Connor, Noel; Smeaton, Alan F. (Association for Computing Machinery (ACM), 2015)
      Conference lecture
      Open Access
      This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based image retrieval. Several experiments are performed using a rapid serial visual presentation ...
    • Improving object segmentation by using EEG signals and rapid serial visual presentation 

      Mohedano, Eva; Healy, Graham; McGuinness, Kevin; Giró Nieto, Xavier; O'Connor, Noel; Smeaton, Alan F. (2015-07-31)
      Article
      Open Access
      This paper extends our previous work on the potential of EEG-based brain computer interfaces to segment salient objects in images. The proposed system analyzes the Event Related Potentials (ERP) generated by the rapid ...
    • Insight Centre for Data Analytics (DCU) at TRECVid 2014: instance search and semantic indexing tasks 

      McGuinness, Kevin; Mohedano, Eva; Zhang, ZhenXing; Hu, Feiyan; Abatal, Rami; Gurrin, Cathal; O'Connor, Noel; Smeaton, Alan F.; Salvador Aguilera, Amaia; Giró Nieto, Xavier; Ventura, Carles (2014)
      Conference report
      Open Access
      Insight-DCU participated in the instance search (INS) and semantic indexing (SIN) tasks in 2014. Two very different approaches were submitted for instance search, one based on features extracted using pre-trained deep ...
    • Insight DCU at TRECVID 2015 

      McGuinness, Kevin; Mohedano, Eva; Salvador Aguilera, Amaia; Zhan, Zhenxing; Marsden, Mark; Wang, Peng; Jargalsaikhan, Iveel; Antony, Joseph; Giró Nieto, Xavier; Satoh, Shin'ichi; O'Connor, Noel; Smeaton, Alan F. (2015)
      Conference lecture
      Restricted access - publisher's policy
      Insight-DCU participated in the instance search (INS), semantic indexing (SIN), and localization tasks (LOC) this year. In the INS task we used deep convolutional network features trained on external data and the query ...
    • Object retrieval with deep convolutional features 

      Mohedano, Eva; Salvador Aguilera, Amaia; McGuinness, Kevin; Giró Nieto, Xavier; O'Connor, Noel; Marqués Acosta, Fernando (IOS Press, 2017-11-23)
      Part of book or chapter of book
      Restricted access - publisher's policy
      Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, ...
    • Object segmentation in images using EEG signals 

      Mohedano, Eva; Healy, Graham; McGuinness, Kevin; Giró Nieto, Xavier; O'Connor, Noel; Smeaton, Alan F. (ACM, 2014)
      Conference lecture
      Open Access
      This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they ...
    • PathGAN: visual scanpath prediction with generative adversarial networks 

      Assens, Marc; Giró Nieto, Xavier; McGuinness, Kevin; O'Connor, Noel (Springer, 2019)
      Conference lecture
      Open Access
      We introduce PathGAN, a deep neural network for visual scanpath prediction trained on adversarial examples. A visual scanpath is defined as the sequence of fixation points over an image defined by a human observer with its ...
    • SaltiNet: scan-path prediction on 360 degree images using saliency volumes 

      Assens, Marc; Giró Nieto, Xavier; McGuinness, Kevin; O'Connor, Noel (IEEE Press, 2018)
      Conference lecture
      Open Access
      We introduce SaltiNet, a deep neural network for scan-path prediction trained on 360-degree images. The model is based on a temporal-aware novel representation of saliency information named the saliency volume. The first ...
    • Scanpath and saliency prediction on 360 degree images 

      Assens Reina, Marc; Giró Nieto, Xavier; McGuinness, Kevin; O'Connor, Noel (2018-06-23)
      Article
      Restricted access - publisher's policy
      We introduce deep neural networks for scanpath and saliency prediction trained on 360-degree images. The scanpath prediction model called SaltiNet is based on a temporal-aware novel representation of saliency information ...
    • Shallow and deep convolutional networks for saliency prediction 

      Pan, Junting; Sayrol Clols, Elisa; Giró Nieto, Xavier; McGuinness, Kevin; O'Connor, Noel (Institute of Electrical and Electronics Engineers (IEEE), 2016)
      Conference lecture
      Restricted access - publisher's policy
      The prediction of salient areas in images has been traditionally addressed with hand-crafted features based on neuroscience principles. This paper, however, addresses the problem with a completely data-driven approach by ...
    • Simple vs complex temporal recurrences for video saliency prediction 

      Linardos, Panagiotis; Mohedano, Eva; Nieto, Juan Jose; O'Connor, Noel; Giró Nieto, Xavier; McGuinness, Kevin (2019)
      Conference lecture
      Restricted access - publisher's policy
      This paper investigates modifying an existing neural network architecture for static saliency prediction using two types of recurrences that integrate information from the temporal domain. The first modification is the ...
    • Wav2Pix: speech-conditioned face generation using generative adversarial networks 

      Cardoso Duarte, Amanda; Roldan, Francisco; Tubau, Miquel; Escur, Janna; Pascual de la Puente, Santiago; Salvador Aguilera, Amaia; Mohedano, Eva; McGuinness, Kevin; Torres Viñals, Jordi; Giró Nieto, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2019)
      Conference lecture
      Restricted access - publisher's policy
      Speech is a rich biometric signal that contains information about the identity, gender and emotional state of the speaker. In this work, we explore its potential to generate face images of a speaker by conditioning a ...
    • Where is my phone?: personal object retrieval from egocentric images 

      Reyes, Cristian; Mohedano, Eva; McGuinness, Kevin; O'Connor, Noel; Giró Nieto, Xavier (Association for Computing Machinery (ACM), 2016)
      Conference lecture
      Restricted access - publisher's policy
      This work presents a retrieval pipeline and evaluation scheme for the problem of finding the last appearance of personal objects in a large dataset of images captured from a wearable camera. Each personal object is modelled ...