User profiles for Ian Stavness
 | Ian StavnessProfessor, Computer Science, University of Saskatchewan Verified email at cs.usask.ca Cited by 5612 |
[HTML][HTML] Deep plant phenomics: a deep learning platform for complex plant phenotyping tasks
JR Ubbens, I Stavness - Frontiers in plant science, 2017 - frontiersin.org
Plant phenomics has received increasing interest in recent years in an attempt to bridge the
genotype-to-phenotype knowledge gap. There is a need for expanded high-throughput …
genotype-to-phenotype knowledge gap. There is a need for expanded high-throughput …
ArtiSynth: A fast interactive biomechanical modeling toolkit combining multibody and finite element simulation
ArtiSynth ( http://www.artisynth.org ) is an open source, Java-based biomechanical simulation
environment for modeling complex anatomical systems composed of both rigid and …
environment for modeling complex anatomical systems composed of both rigid and …
[HTML][HTML] Global wheat head detection (GWHD) dataset: A large and diverse dataset of high-resolution RGB-labelled images to develop and benchmark wheat head …
The detection of wheat heads in plant images is an important task for estimating pertinent
wheat traits including head population density and head characteristics such as health, size, …
wheat traits including head population density and head characteristics such as health, size, …
Improving object counting with heatmap regulation
S Aich, I Stavness - arXiv preprint arXiv:1803.05494, 2018 - arxiv.org
In this paper, we propose a simple and effective way to improve one-look regression models
for object counting from images. We use class activation map visualizations to illustrate the …
for object counting from images. We use class activation map visualizations to illustrate the …
Wilds: A benchmark of in-the-wild distribution shifts
Distribution shifts—where the training distribution differs from the test distribution—can
substantially degrade the accuracy of machine learning (ML) systems deployed in the wild. …
substantially degrade the accuracy of machine learning (ML) systems deployed in the wild. …
[HTML][HTML] The use of plant models in deep learning: an application to leaf counting in rosette plants
Deep learning presents many opportunities for image-based plant phenotyping. Here we
consider the capability of deep convolutional neural networks to perform the leaf counting task. …
consider the capability of deep convolutional neural networks to perform the leaf counting task. …
Extending the wilds benchmark for unsupervised adaptation
Machine learning systems deployed in the wild are often trained on a source distribution but
deployed on a different target distribution. Unlabeled data can be a powerful point of …
deployed on a different target distribution. Unlabeled data can be a powerful point of …
Leaf counting with deep convolutional and deconvolutional networks
S Aich, I Stavness - … of the IEEE international conference on …, 2017 - openaccess.thecvf.com
In this paper, we investigate the problem of counting rosette leaves from an RGB image, an
important task in plant phenotyping. We propose a data-driven approach for this task …
important task in plant phenotyping. We propose a data-driven approach for this task …
[HTML][HTML] Global wheat head detection 2021: An improved dataset for benchmarking wheat head detection methods
The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled
193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition …
193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition …
Automatic prediction of tongue muscle activations using a finite element model
Computational modeling has improved our understanding of how muscle forces are coordinated
to generate movement in musculoskeletal systems. Muscular-hydrostat systems, such …
to generate movement in musculoskeletal systems. Muscular-hydrostat systems, such …