Category: Publication

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 high-throughput and in situ methods to measure TLP. We developed hyperspectral pressure–volume curves (PV curves) […]

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 target. In these cases what is the classifier to do? In this paper we define […]

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 train a fully supervised semantic classifier. Post-hoc attention mechanisms, such as class activation mapping (CAM), […]

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 physical properties like root length, volume, and surface area. HSI provides a more complete spectral […]

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 species, airborne remote sensing can cover areas containing millions of trees at high spatial resolution. […]

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 sensitive to cold storage and can develop chilling injury with symptoms such as abnormal ripening, […]

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. In this work, we propose to address this problem. Generative Adversarial Networks (GANs) are a […]

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 of trees. To train computer vision models, ground-based species labels are combined with airborne reflectance […]

Abstract: Target detection is a paramount task in remote sensing which aims to detect points of interest from a set of data. A crucial aspect attributed to the success of target detection methods is the representation of the data which goes into them. Consequentially, feature representation learning has been explored extensively in the literature [1, […]

Abstract: Root system architectures are complex and challenging to characterize effectively for agronomic and ecological discovery. We propose a new method, Spatial and Texture Analysis of Root System distribution with Earth mover’s Distance (STARSEED), for comparing root system distributions that incorporates spatial information through a novel application of the Earth Mover’s Distance (EMD). We illustrate […]