9 citations · 11 across the 2 of their papers we have counts for
5 papers · 1 filter
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…
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…
Presenting an extensive lab- and field-image dataset of crops and weeds for computer vision tasks in agriculture
Michael A. Beck, Chen-Yi Liu, Christopher P. Bidinosti +3
We present two large datasets of labelled plant-images that are suited towards the training of machine learning and computer vision models. The first dataset encompasses as the day…
An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture
Michael A. Beck, Chen-Yi Liu, Christopher P. Bidinosti +3
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 agric…