260 citations · 477 across the 11 of their papers we have counts for
14 papers
PRMI: A Dataset of Minirhizotron Images for Diverse Plant Root Study
Weihuang Xu, Guohao Yu, Yiming Cui +10
Understanding a plant's root system architecture (RSA) is crucial for a variety of plant science problem domains including sustainability and climate adaptation. Minirhizotron (MR)…
The Weakly-Labeled Rand Index
Dylan Stewart, Anna Hampton, Alina Zare +2
Synthetic Aperture Sonar (SAS) surveys produce imagery with large regions of transition between seabed types. Due to these regions, it is difficult to label and segment the imagery…
Explainable Systematic Analysis for Synthetic Aperture Sonar Imagery
Sarah Walker, Joshua Peeples, Jeff Dale +2
In this work, we present an in-depth and systematic analysis using tools such as local interpretable model-agnostic explanations (LIME) (arXiv:1602.04938) and divergence measures t…
Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification
Joshua Peeples, Sarah Walker, Connor McCurley +3
Feature representation is an important aspect of remote-sensing based image classification. While deep convolutional neural networks are able to effectively amalgamate information,…
Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM
Guohao Yu, Alina Zare, Weihuang Xu +4
We present a multiple instance learning class activation map (MIL-CAM) approach for pixel-level minirhizotron image segmentation given weak image-level labels. Minirhizotrons are u…
Outlier Detection through Null Space Analysis of Neural Networks
Matthew Cook, Alina Zare, Paul Gader
Many machine learning classification systems lack competency awareness. Specifically, many systems lack the ability to identify when outliers (e.g., samples that are distinct from…
Super Resolution for Root Imaging
Jose F. Ruiz-Munoz, Jyothier K. Nimmagadda, Tyler G. Dowd +2
High-resolution cameras have become very helpful for plant phenotyping by providing a mechanism for tasks such as target versus background discrimination, and the measurement and a…
Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +6
The spectral signatures of the materials contained in hyperspectral images, also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or…
Histogram Layers for Texture Analysis
Joshua Peeples, Weihuang Xu, Alina Zare
An essential aspect of texture analysis is the extraction of features that describe the distribution of values in local, spatial regions. We present a localized histogram layer for…
Hybrid data-driven physics model-based framework for enhance cyber-physical smart grid security
Cody Ruben, Surya Dhulipala, Keerthiraj Nagaraj +5
This paper presents a hybrid data-driven physics model-based framework for real time monitoring in smart grids. As the power grid transitions to the use of smart grid technology, i…
Peanut Maturity Classification using Hyperspectral Imagery
Sheng Zou, Yu-Chien Tseng, Alina Zare +3
Seed maturity in peanut (Arachis hypogaea L.) determines economic return to a producer because of its impact on seed weight (yield), and critically influences seed vigor and other…
Multi-Target Multiple Instance Learning for Hyperspectral Target Detection
Susan Meerdink, James Bocinsky, Alina Zare +4
In remote sensing, it is often challenging to acquire or collect a large dataset that is accurately labeled. This difficulty is usually due to several issues, including but not lim…
Overcoming Small Minirhizotron Datasets Using Transfer Learning
Weihuang Xu, Guohao Yu, Alina Zare +6
Minirhizotron technology is widely used for studying the development of roots. Such systems collect visible-wavelength color imagery of plant roots in-situ by scanning an imaging s…
Root Identification in Minirhizotron Imagery with Multiple Instance Learning
Guohao Yu, Alina Zare, Hudanyun Sheng +4
In this paper, multiple instance learning (MIL) algorithms to automatically perform root detection and segmentation in minirhizotron imagery using only image-level labels are propo…