Browsing Department of Applied Computer Science by Author "Henry, Christopher J."
Now showing items 1-13 of 13
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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 (Taylor & Francis, 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 comprehensive review of 3D convolutional neural network-based classification techniques of diseased and defective crops using non-UAV-based hyperspectral images
Noshiri, Nooshin; Beck, Michael A.; Bidinosti, Christopher P.; Henry, Christopher J. (Elsevier B.V., 2023-09-14)Hyperspectral imaging (HSI) is a non-destructive and contactless technology that provides valuable information about the structure and composition of an object. It has the ability to capture detailed information about the ... -
A computational discussion on brain topodynamics: Comment on "Topodynamics of metastable brains" by Arturo Tozzi et al.
Henry, Christopher J. (Elsevier, 2017-04-25) -
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, ... -
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 ... -
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.; Godee, 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 ... -
Inside out: transforming images of lab-grown plants for machine learning applications in agriculture
Krosney, Alexander E.; Sotoodeh, Parsa; Henry, Christopher J.; Beck, Michael A.; Bidinosti, Christopher P. (Frontiers, 2023-07-06)Machine learning tasks often require a significant amount of training data for the resultant network to perform suitably for a given problem in any domain. In agriculture, dataset sizes are further limited by phenotypical ... -
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 ... -
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 ... -
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 ... -
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 ... -
Quantifying nearness in visual spaces
Henry, Christopher J.; Ramanna, Sheela; Levy, Daniel (Taylor & Francis, 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 ... -
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 ...