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Fusarium head blight detection, spikelet estimation, and severity assessment in wheat using 3D convolutional neural networks
(Canadian Science Publishing, 2024-04-10)
Fusarium head blight (FHB) is one of the most significant diseases affecting wheat and other small-grain cereals worldwide. Developing FHB-resistant cultivars is critical but requires field and greenhouse disease assessment, ...
An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture
(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 ...
A Descriptive Tolerance Nearness Measure for Performing Graph Comparison
(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, ...
Inside out: transforming images of lab-grown plants for machine learning applications in agriculture
(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 ...
Metric free nearness measure using description-based neighbourhoods
(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 ...
Automated LULC Map Production using Deep Neural Networks
(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 ...
Quantifying nearness in visual spaces
(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
(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 ...
Leveraging Guided Backpropagation to Select Convolutional Neural Networks for Plant Classification
(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 ...