40 citations · 57 across the 10 of their papers we have counts for
11 papers
Generative diffusion models for agricultural AI: plant image generation, indoor-to-outdoor translation, and expert preference alignment
Da Tan, Michael Beck, Christopher P. Bidinosti +2
The success of agricultural artificial intelligence depends heavily on large, diverse, and high-quality plant image datasets, yet collecting such data in real field conditions is c…
A Low-Cost Photogrammetry System for 3D Plant Modeling and Phenotyping
Joe Hrzich, Michael A. Beck, Christopher P. Bidinosti +3
We present an open-source, low-cost photogrammetry system for 3D plant modeling and phenotyping. The system uses a structure-from-motion approach to reconstruct 3D representations…
Automated Linear Disturbance Mapping via Semantic Segmentation of Sentinel-2 Imagery
Andrew M. Nagel, Anne Webster, Christopher Henry +5
In Canada's northern regions, linear disturbances such as roads, seismic exploration lines, and pipelines pose a significant threat to the boreal woodland caribou population (Rangi…
Strategies and impact of learning curve estimation for CNN-based image classification
Laura Didyk, Brayden Yarish, Michael A. Beck +2
Learning curves are a measure for how the performance of machine learning models improves given a certain volume of training data. Over a wide variety of applications and models it…
A comprehensive review of 3D convolutional neural network-based classification techniques of diseased and defective crops using non-UAV-based hyperspectral images
Nooshin Noshiri, Michael A. Beck, Christopher P. Bidinosti +1
Hyperspectral imaging (HSI) is a non-destructive and contactless technology that provides valuable information about the structure and composition of an object. It can capture deta…
Fusarium head blight detection, spikelet estimation, and severity assessment in wheat using 3D convolutional neural networks
Oumaima Hamila, Christopher J. Henry, Oscar I. Molina +2
Fusarium head blight (FHB) is one of the most significant diseases affecting wheat and other small grain cereals worldwide. The development of resistant varieties requires the labo…
Semantically-consistent Landsat 8 image to Sentinel-2 image translation for alpine areas
M. Sokolov, J. L. Storie, C. J. Henry +5
The availability of frequent and cost-free satellite images is in growing demand in the research world. Such satellite constellations as Landsat 8 and Sentinel-2 provide a massive…
Exploration of Convolutional Neural Network Architectures for Large Region Map Automation
R. M. Tsenov, C. J. Henry, J. L. Storie +3
Deep learning semantic segmentation algorithms have provided improved frameworks for the automated production of Land-Use and Land-Cover (LULC) maps, which significantly increases…
Inside Out: Transforming Images of Lab-Grown Plants for Machine Learning Applications in Agriculture
A. E. Krosney, P. Sotoodeh, C. J. Henry +2
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…
Investigating classification learning curves for automatically generated and labelled plant images
Michael A. Beck, Christopher P. Bidinosti, Christopher J. Henry +1
In the context of supervised machine learning a learning curve describes how a model's performance on unseen data relates to the amount of samples used to train the model. In this…
The TerraByte Client: providing access to terabytes of plant data
Michael A. Beck, Christopher P. Bidinosti, Christopher J. Henry +1
In this paper we demonstrate the TerraByte Client, a software to download user-defined plant datasets from a data portal hosted at Compute Canada. To that end the client offers two…