Abstract: Heterogeneous data fusion can enhance the robustness and accuracy of an algorithm on a given task. However, due to the difference in various modalities, aligning the sensors and embedding their information into discriminative and compact representations is challenging. In… Read More
PublicationPublication
Continental-scale hyperspectral tree species classification in the United States National Ecological Observatory Network
Abstract: Advances in remote sensing imagery and machine learning applications unlock the potential for developing algorithms for species classification at the level of individual tree crowns at unprecedented scales. However, most approaches to date focus on site-specific applications and a… Read More
Connecting The Past And The Present: Histogram Layers For Texture Analysis
Abstract: Feature engineering often plays a vital role in the fields of computer vision and machine learning. A few common examples of engineered features include histogram of oriented gradients (HOG) (Dalal and Triggs, 2005), local binary patterns (LBP) (Ojala et… Read More
Bag-level Classification Network for Infrared Target Detection
Abstract: Aided target detection in infrared data has proven an important area of investigation for both military and civilian applications. While target detection at the object or pixel-level has been explored extensively, existing approaches require precisely-annotated data which is often… Read More
Computer vision for assessing species color pattern variation from web-based community science images
Abstract: Openly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a workflow and computer vision model… Read More
PRMI: A Dataset of Minirhizotron Images for Diverse Plant Root Study
Abstract: 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) technology is a widely-used approach for phenotyping RSA non-destructively by capturing root imagery over time.… Read More
Image-to-Height Domain Translation for Synthetic Aperture Sonar
Abstract: Synthetic aperture sonar (SAS) intensity statistics are dependent upon the sensing geometry at the time of capture. Estimating bathymetry from acoustic surveys is challenging. While several methods have been proposed to estimate seabed relief via intensity, we develop the… Read More
Jointly Optimized Spatial Histogram UNET Architecture (JOSHUA) for Adipose Tissue Segmentation
Abstract: Objective: We quantify adipose tissue deposition at surgical sites as a function of biomaterial implantation. Impact Statement: To our knowledge, this study is the first investigation to apply convolutional neural network (CNN) models to identify and segment adipose tissue… Read More
Robust Semi-Supervised Classification using GANs with Self-Organizing Maps
Abstract: Generative adversarial networks (GANs) have shown tremendous promise in learning to generate data and effective at aiding semi-supervised classification. However, to this point, semi-supervised GAN methods make the assumption that the unlabeled data set contains only samples of the… Read More
Learnable Adaptive Cosine Estimator (LACE) for Image Classification
Abstract: In this work, we propose a new loss to improve feature discriminability and classification performance. Motivated by the adaptive cosine/coherence estimator [42] (ACE), our proposed method incorporates angular information that is inherently learned by artificial neural networks. Our learnable… Read More