Abstract: Estimating potato tuber mass and size grading with computer vision can help breeders, farmers, and potato processing units reduce manual labor for potato post-harvest handling through optimized technology. The objective of the study was to estimate potato tuber mass… Read More
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Quantifying Heterogeneous Ecosystem Services with Multi-Label Soft Classification
Abstract: Understanding and quantifying ecosystem services are crucial for sustainable environmental management, conservation efforts, and policy-making. The advancement of remote sensing technology and machine learning techniques has greatly facilitated this process. Yet, ground truth labels, such as biodiversity, are very… Read More
Individual canopy tree species maps for the National Ecological Observatory Network
Abstract: The ecology of forest ecosystems depends on the composition of trees. Capturing fine-grained information on individual trees at broad scales provides a unique perspective on forest ecosystems, forest restoration and responses to disturbance. Individual tree data at wide extents… Read More
Estimating Soil Mineral Nitrogen from Data-sparse Field Experiments using Crop Model-guided Deep Learning Approach
Abstract: Sandy soils are susceptible to excessive nitrogen (N) leaching under intensive crop production which is linked with the soil’s low nutrient holding capacity and high-water infiltration rate. Estimating soil mineral nitrogen (SMN) at the daily time-step is crucial in… Read More
Hyperspectral signals in the soil: Plant–soil hydraulic connection and disequilibrium as mechanisms of drought tolerance and rapid recovery
Abstract: Predicting soil water status remotely is appealing due to its low cost and large-scale application. During drought, plants can disconnect from the soil, causing disequilibrium between soil and plant water potentials at pre-dawn. The impact of this disequilibrium on… Read More
Elicitating Challenges and User Needs Associated with Annotation Software for Plant Phenotyping
Abstract: Artificial Intelligence (AI) has been enhancing data analysis efficiency and accuracy during plant phenotyping, which is vital for tackling global agricultural and environmental challenges. Designing a reliable AI system to assist precise plant phenotyping begins with high-quality phenotypic feature… Read More
Dealing with imperfect data for invasive species detection using multispectral imagery
Abstract: Detection and monitoring invasive species can provide valuable ecological information to guide management decisions. Multispectral imagery remote sensing may be an ideal tool to address this problem by providing accurate and affordable repeat imagery. However, developing training datasets for… Read More
Spectral ecophysiology: hyperspectral pressure–volume curves to estimate leaf turgor loss
Abstract: Turgor loss point (TLP) is an important proxy for plant drought tolerance, species habitat suitability, and drought-induced plant mortality risk. Thus, TLP serves as a critical tool for evaluating climate change impacts on plants, making it imperative to develop… Read More
Null Space Analysis for Detecting Unknown Objects During Automatic Target Recognition Tasks in Sonar Data
Abstract: During automatic target recognition once a detector has found points of interest the classifier is then tasked with identifying target objects from non-target objects. However, occasionally the detector may find something that is neither known false alarm nor expected… Read More
Segmentation Pseudo-label Generation using the Multiple Instance Learning Choquet Integral
Abstract: Weakly supervised target detection and semantic segmentation (WSSS) approaches aim at learning object or pixel level classification labels from imprecise, uncertain, or ambiguous data annotations. A crucial step in WSSS is to produce pseudolabels which can be used to… Read More