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
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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
HyperPRI: A Dataset of Hyperspectral Images for Underground Plant Root Study
Abstract: Collecting and analyzing hyperspectral imagery (HSI) of plant roots over time can enhance our understanding of their function, responses to environmental factors, turnover, and relationship with the rhizosphere. Current belowground red-green-blue (RGB) root imaging studies infer such functions from… Read More
Individual tree crown 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 allows an unprecedented view of forest ecosystems, forest restoration and responses to disturbance. To create detailed maps of tree… Read More
Hyperspectral image analysis for the evaluation of chilling injury in avocado fruit during cold storage
Abstract: Many vegetables and fruit are sensitive to storage at lower temperatures and experience chilling injury that can result in internal disorder, leading to postharvest waste and economic loss. Most tropical and subtropical fruit, such as avocado and mango, are… Read More
Robust GANs for Semi-Supervised Classification
Abstract: Semi-supervised learning attempts to take advantage of the large amount of unlabeled information present in many datasets. However, unlabeled data will often contain samples outside the classes of interest. Many existing semi-supervised learning methods do not address this issue.… Read More
Capturing long-tailed individual tree diversity using an airborne imaging and a multi-temporal hierarchical model
Abstract: Measuring forest biodiversity using terrestrial surveys is expensive and can only capture common species abundance in large heterogeneous landscapes. In contrast, combining airborne imagery with computer vision can generate individual tree data at the scales of hundreds of thousands… Read More