Congratulations to GatorSense alumna, Xiaoxiao Du! Her paper, titled “Multi-resolution Multi-modal Sensor Fusion For Remote Sensing Data with Label Uncertainty”, was recently published in IEEE Transactions on Geoscience and Remote Sensing. Check it out here!
Tag: classification
Multi-Target Multiple Instance Learning for Hyperspectral Target Detection
Abstract: In remote sensing, it is often challenging to acquire or collect a large dataset that is accurately labeled. This difficulty is usually due to several issues, including but not limited to the study site’s spatial area and accessibility, errors… Read More
Master’s Defenses!
Congratulations to our labmates, Hudanyun Sheng and Princess Lyons, for successful Master’s defenses! Hudanyun conducted work on “Switchgrass Genotype Classification using Hyperspectral Imagery”, while Princess investigated “Anomaly and Target Detection in Synthetic Aperture Sonar”. Great job, you two!
Peanut Maturity Classification using Hyperspectral Imagery
Abstract: Seed maturity in peanut ( Arachis hypogaea L.) determines economic return to a producer because of its impact on seed weight, and critically influences seed vigor and other quality characteristics. During seed development, the inner mesocarp layer of the… Read More
Classifying California plant species temporally using airborne hyperspectral imagery
Abstract: Accurate knowledge of seasonal and inter-annual distributions of plant species is required for many research and management agendas that track ecosystem health. Airborne imaging spectroscopy data have been used successfully to map plant species, but often only in a… Read More
Developing Spectral Libraries Using Multiple Target Multiple Instance Adaptive Cosine/Coherence Estimator
Abstract: Traditional methods of developing spectral libraries for unmixing hyperspectral images tend to require domain knowledge of the study area and the material’s spectra. In this paper, we propose using the Multiple Target Multiple Instance Adaptive Cosine/Coherence Estimator (Multi-Target MI-ACE)… Read More
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
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
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