Abstract: Wide-band Electromagnetic Induction Sensors (WEMI) have been used for a number of years in subsurface detection of explosive hazards. While WEMI sensors have proven effective at localizing objects exhibiting large magnetic responses, detecting objects lacking or containing very low… Read More
PublicationPublication
Overcoming Small Minirhizotron Datasets Using Transfer Learning
Abstract: 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 system within a clear tube driven into the soil. Automated analysis of root systems… Read More
RhizoVision Crown: An Integrated Hardware and Software Platform for Root Crown Phenotyping
Abstract: Root crown phenotyping measures the top portion of crop root systems and can be used for marker-assisted breeding, genetic mapping, and understanding how roots influence soil resource acquisition. Several imaging protocols and image analysis programs exist, but they are… Read More
Root Identification in Minirhizotron Imagery with Multiple Instance Learning
Abstract: In this paper, multiple instance learning (MIL) algorithms to automatically perform root detection and segmentation in minirhizotron imagery using only image-level labels are proposed. Root and soil characteristics vary from location to location, thus, supervised machine learning approaches that… Read More
Three dimensional reconstruction of plant roots via low energy X-ray computed tomography
Abstract: Plant roots are vital organs for water and nutrient uptake. The structure and spatial distribution of plant roots in the soil affects a plant’s physiological functions such as soil-based resource acquisition, yield and its ability to live under abiotic… Read More
Complex Scene Classification of PoLSAR Imagery Based on a Self-Paced Learning Approach
Abstract: Existing polarimetric synthetic aperture radar (PolSAR) image classification methods cannot achieve satisfactory performance on complex scenes characterized by several types of land cover with significant levels of noise or similar scattering properties across land cover types. Hence, we propose… Read More
Hyperspectral Tree Crown Classification Using the Multiple Instance Adaptive Cosine Estimator
Abstract: Tree species classification using hyperspectral imagery is a challenging task due to the high spectral similarity between species and large intra-species variability. This paper proposes a solution using the Multiple Instance Adaptive Cosine Estimator (MI-ACE) algorithm. MI-ACE estimates a… Read More
A fully learnable context-driven object-based model for mapping land cover using multi-view data from unmanned aircraft systems
Abstract: Context information is rarely used in the object-based landcover classification. Previous models that attempted to utilize this information usually required the user to input empirical values for critical model parameters, leading to less optimal performance. Multi-view image information is… Read More
A Target Classification Algorithm for Underwater Synthetic Aperture Sonar Imagery
Abstract: The ability to discern the characteristics of the seafloor has many applications. Due to minimal visibility, Synthetic Aperture Sonar Imagery (SAS) uses sonar to produce a texture map of the seabed below. In this paper, we discuss an approach… Read More
Fractal Analysis of Seafloor Textures for Target Detection in Synthetic Aperture Sonar Imagery
Abstract: Fractal analysis of an image is a mathematical approach to generate surface related features from an image or image tile that can be applied to image segmentation and to object recognition. In undersea target countermeasures, the targets of interest… Read More