Recent Submissions

  • Leveraging Guided Backpropagation to Select Convolutional Neural Networks for Plant Classification

    Mostafa, Sakib;Mondal, Debajyoti;Beck, Michael A.;Bidinosti, Christopher P.;Henry, Christopher J.;Stavness, Ian (2022-05-11)
    The development of state-of-the-art convolutional neural networks (CNN) has allowed researchers to perform plant classification tasks previously thought impossible and rely on human judgment. Researchers often develop ...
  • Descriptive Topological Spaces for Performing Visual Search

    Yu, Jiajie;Henry, Christopher J. (Springer,2019-02-02)
    This article presents an approach to performing the task of visual search in the context of descriptive topological spaces. The presented algorithm forms the basis of a descriptive visual search system (DVSS) that is based ...
  • A Descriptive Tolerance Nearness Measure for Performing Graph Comparison

    Henry, Christopher J.;Awais, Syed Aqeel (IOS Press,2018-11-03)
    This article proposes the tolerance nearness measure (TNM) as a computationally reduced alternative to the graph edit distance (GED) for performing graph comparisons. The TNM is defined within the context of near set theory, ...
  • An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture

    Beck, Michael A.;Liu, Chen-Yi;Bidinosti, Christopher P.;Henry, Christopher J.;去dee, Cara M.;Ajmani, Manisha (PLOS,2020-12-17)
    A lack of sufficient training data, both in terms of variety and quantity, is often the bottleneck in the development of machine learning (ML) applications in any domain. For agricultural applications, ML-based models ...
  • Signature-based perceptual nearness: Application of near sets to image retrieval

    Henry, Christopher J.;Ramanna, Sheela (Birkhäuser,2013)
    This paper presents a signature-based approach to quantifying perceptual nearness of images. A signature is defined as a set of descriptors, where each descriptor consists of a real-valued feature vector associated with a ...
  • Quantifying nearness in visual spaces

    Henry, Christopher J.;Ramanna, Sheela;Levy, Daniel (泰勒和弗朗西斯,2013)
    Cybernetic vision systems can be deployed in problem domains where the goal is to achieve results similar to those produced by humans. Fundamentally, these problems consist of evaluation of image content between sets of ...
  • Perception-based image classification: Framework for perception-based cybernetics

    Henry, Christopher;Peters, James F. (Emerald Insight,2010-08-24)
    Purpose: The purpose of this paper is to present near set theory using the perceptual indiscernibility and tolerance relations, to demonstrate the practical application of near set theory to the image correspondence problem, ...
  • Neighbourhood-based vision systems

    Henry, Christopher J.;Peters, James F. (Taylor and Francis,2011)
    The problem presented in this paper is how to find similarities between digital images useful in design cybernetic vision systems. The solution to this problem stems from a neighbourhood based vision system. A neighbourhood ...
  • Metric free nearness measure using description-based neighbourhoods

    Henry, Christopher J. (Springer,2013-02-26)
    The focus of this paper is on a metric free nearness measure for quantifying the descriptive nearness of digital images. Regions of Interest (ROI) play an important role in discerning perceptual similarity within a single ...
  • Measuring the nearness of layered flow graphs: Application to Content Based Image Retrieval

    Kaur, Kanwarpreet;Ramanna, Sheela;Henry, Christopher (IOS Press,2016-03-01)
    Rough set based flow graphs represent the flow of information for a given data set where branches of these could be constructed as decision rules. However, in the recent years, the concept of flow graphs has been applied ...
  • Automated LULC Map Production using Deep Neural Networks

    Henry, Christopher J.;Storie, Christopher;Palaniappan, Muthu;Alhassan, Victor;Swamy, Mallikarjun;Aleshinloye, Damilola;Curtis, Andrew;Kima, Daeyoun (泰勒和弗朗西斯,2019-01-17)
    This article presents an approach to automating the creation of land-use/land-cover classification (LULC) maps from satellite images using deep neural networks that were developed to perform semantic segmentation of natural ...
  • A Deep Learning Framework: Land-Use/Land-Cover Mapping and Analysis using Multispectral Satellite Imagery

    Alhassan, Victor;Henry, Christopher;Ramanna, Sheela;Storie, Christopher (Springer,2019-07-17)
    In this article, we present an approach to land-use and land-cover (LULC) mapping from multispectral satellite images using deep learning methods. The terms satellite image classification and map production, although used ...
  • Perceptual image analysis

    Henry, C.;Peters, J. F. (Inderscience Enterprises Ltd.,2010)
    本文考虑的问题是ext之一racting perceptually relevant information from groups of objects based on their descriptions. Object descriptions are qualitatively represented by feature-value vectors ...
  • Arthritic hand-finger movement similarity measurements: Tolerance near set approach

    Henry, Christopher (Hindawi Publishing Corporation,2011)
    The problem considered in this paper is how to measure the degree of resemblance between nonarthritic and arthritic hand movements during rehabilitation exercise. The solution to this problem stems from recent work on a ...
  • Neighbourhoods, classes, and near sets

    Henry, Christopher J. (Applied Mathematical Sciences,,2011)
    The article calls attention to the relationship between neighbourhoods and tolerance classes in the foundations of tolerance near sets. A particular form of tolerance relation is given by way of introduction to descriptively ...
  • Automated Land Use and Land Cover Map Production: A Deep Learning Framework

    Alhassan, Victor (University of WinnipegUniversity of Winnipeg,2018-10-19)
    In this thesis, we present an approach to automating the creation of land use and land cover (LULC) maps from satellite images using deep neural networks that were developed to perform semantic segmentation of natural ...