Skip to Content

Search

You searched for: breckon Remove constraint breckon

Search Results

  1. Fire Image Data Set for Dunnings 2018 study - PNG still image set [Download]

    Title: Fire Image Data Set for Dunnings 2018 study - PNG still image set
    Contributors: Data curator: Dunnings, Andy (Durham University, UK)
    Data collector: Dunnings, Andy (Durham University, UK)
    Creator: Dunnings, Andy (Durham University, UK)
    Editor: Breckon, Toby (Durham University, UK)
    Contact person: Breckon, Toby (Durham University, UK)
    Description:
    Keywords: Fire detection, Deep learning, Machine learning, Computer vision
    Date Uploaded: 30 July 2018
  2. Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments

    Title: Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments
    Contributors: Creator: Maciel-Pearson,Bruna (Durham University)
    Creator: Breckon, Toby (Durham University)
    Description:
    Keywords: unstructured environment, robot guidance, flight guidance, unmanned aerial vehicle, multi-task regression learning, deep learning, drone, unmanned aerial system
    Date Uploaded:
  3. On The Impact Of Varying Region Proposal Strategies For Raindrop Detection And Classification Using Convolutional Neural Networks - Supporting Materials

    Title: On The Impact Of Varying Region Proposal Strategies For Raindrop Detection And Classification Using Convolutional Neural Networks - Supporting Materials
    Contributors: Data collector: Guo, Tiancheng (Durham Univesity, UK)
    Data curator: Guo, Tiancheng (Durham Univesity, UK)
    Creator: Breckon, Toby (Durham University, UK)
    Data collector: Breckon, Toby (Durham University, UK)
    Data curator: Breckon, Toby (Durham University, UK)
    Editor: Breckon, Toby (Durham University, UK)
    Description:
    Keywords: Computer vision, Convolutional neural networks (CNN), Raindrop detection, Rain detection, Rain removal, Rain noise removal, Rain interference, Scene context, Raindrop saliency, Rain classification, Deep learning
    Date Uploaded:
  4. Pretrained Neural Network Models for Guo 2018 study - TensorFlow format [Download]

    Title: Pretrained Neural Network Models for Guo 2018 study - TensorFlow format
    Contributors: Creator: Guo, Tiancheng (Durham University, UK)
    Data collector: Guo, Tiancheng (Durham University, UK)
    Data curator: Guo, Tiancheng (Durham University, UK)
    Contact person: Breckon, Toby (Durham University, UK)
    Data curator: Breckon, Toby (Durham University, UK)
    Editor: Breckon, Toby (Durham University, UK)
    Description:
    Keywords: Computer vision, Raindrop detection, Rain detection, Rain removal, Rain noise removal, Rain interference, Scene context, Raindrop saliency, Rain classification, Convolutional neural network (CNN), Deep learning
    Date Uploaded: 25 November 2018
  5. Rain Drop Image Data Set for Guo 2018 study - still image set [Download]

    Title: Rain Drop Image Data Set for Guo 2018 study - still image set
    Contributors: Creator: Guo, Tiancheng (Durham University, UK)
    Data collector: Guo, Tiancheng (Durham University, UK)
    Data curator: Guo, Tiancheng (Durham University, UK)
    Contact person: Breckon, Toby (Durham University, UK)
    Data curator: Breckon, Toby (Durham University, UK)
    Editor: Breckon, Toby (Durham University, UK)
    Description:
    Keywords: Computer vision, Raindrop detection, Rain detection, Rain removal, Rain noise removal, Rain interference, Scene context, Raindrop saliency, Rain classification, Convolutional neural network (CNN), Deep learning
    Date Uploaded: 25 November 2018
  6. Pretrained Neural Network Models for Dunnings 2018 study - TensorFlow format [Download]

    Title: Pretrained Neural Network Models for Dunnings 2018 study - TensorFlow format
    Contributors: Creator: Dunnings, Andy (Durham University, UK)
    Editor: Dunnings, Andy (Durham University, UK)
    Contact person: Breckon, Toby (Durham University, UK)
    Editor: Breckon, Toby (Durham University, UK)
    Description:
    Keywords: Convolutional Neural Network
    Date Uploaded: 26 July 2018
  7. Real-time traversable surface detection by colour space fusion and temporal analysis - Evaluation Dataset [Download]

    Title: Real-time traversable surface detection by colour space fusion and temporal analysis - Evaluation Dataset
    Contributors: Contact person: Breckon, Toby P. (Durham University, UK)
    Creator: Breckon, Toby P. (Durham University, UK)
    Creator: Katramados, Ioannis (Cranfield University, UK)
    Description: Data set from research paper: Real-Time Traversable Surface Detection by Colour Space Fusion and Temporal Analysis (I. Katramados, S. Crumpler, T.P. Breckon), In Proc. International Conference on Computer Vision Systems, Springer, Volume 5815, pp. 265-274, 2009. Previously released (2009-2015) as zip file download from personal web page of the authors (Katramados / Breckon).
    Keywords: computer vision, image processing, image analysis, robotics, path detection, robot guidance, traversable pathway, terrain classification, road following, robotic navigation
    Date Uploaded: 3 December 2015
  8. Improved 3D Sparse Maps for High-performance Structure from Motion with Low-cost Omnidirectional Robots - Evaluation Dataset [Download]

    Title: Improved 3D Sparse Maps for High-performance Structure from Motion with Low-cost Omnidirectional Robots - Evaluation Dataset
    Contributors: Creator: Breckon, Toby P. (Durham University, UK)
    Creator: Cavestany, Pedro (Durham University, UK)
    Contact person: Breckon, Toby P. (Durham University, UK)
    Description: Data set used in research paper doi:10.1109/ICIP.2015.7351744
    Keywords: Structure from motion, Mobile robot, Omnidirectional, Noise, Feature filtering
    Date Uploaded: 21 January 2016
  9. Neural network checkpoints [Download]

    Title: Neural network checkpoints
    Contributors: Creator: Atapour-Abarghouei, Amir (Durham University, UK)
    Creator: Breckon, Toby P. (Durham University, UK)
    Description: Neural network checkpoints associated with the work entitled: Real-time monocular depth estimation using synthetic data with domain adaptation via image style transfer / written by A. Atapour-Abarghouei and T.P. Breckon. -- In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2018 : Salt Lake City, Utah).
    Keywords: Computer vision, Image processing, Monocular depth estimation, Image style transfer, Domain adaptation
    Date Uploaded: 24 May 2018
  10. Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach [Neural Network Weights] [Download]

    Title: Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach [Neural Network Weights]
    Contributors: Creator: Atapour-Abarghouei, Amir (Durham University, UK)
    Contact person: Atapour-Abarghouei, Amir (Durham University, UK)
    Editor: Atapour-Abarghouei, Amir (Durham University, UK)
    Contact person: Breckon, Toby P. (Durham University, UK)
    Editor: Breckon, Toby P. (Durham University, UK)
    Description: The data file has been created using PyTorch ( https://pytorch.org
    ) and contains the weights of a generative model trained to perform monocular depth estimation and semantic segmentation. The file is needed as part of the pipeline for the project at  https://github.com/atapour/temporal-depth-segmentation
    Instructions on how the file can be used and how the code is run can also be found at  https://github.com/atapour/temporal-depth-segmentation
    Keywords: Monocular Depth Estimation, Semantic Segmentation, Temporal Consistency, Computer Vision
    Date Uploaded: 15 March 2019