39 citations · 191 across the 29 of their papers we have counts for
23 papers · 1 filter
Shared Manifold Learning Using a Triplet Network for Multiple Sensor Translation and Fusion with Missing Data
Aditya Dutt, Alina Zare, Paul Gader
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 em…
Histogram Layers for Synthetic Aperture Sonar Imagery
Joshua Peeples, Alina Zare, Jeffrey Dale +1
Synthetic aperture sonar (SAS) imagery is crucial for several applications, including target recognition and environmental segmentation. Deep learning models have led to much succe…
Image-to-Height Domain Translation for Synthetic Aperture Sonar
Dylan Stewart, Shawn Johnson, Alina Zare
Observations of seabed texture with synthetic aperture sonar are dependent upon several factors. In this work, we focus on collection geometry with respect to isotropic and anisotr…
Learnable Adaptive Cosine Estimator (LACE) for Image Classification
Joshua Peeples, Connor McCurley, Sarah Walker +2
In this work, we propose a new loss to improve feature discriminability and classification performance. Motivated by the adaptive cosine/coherence estimator (ACE), our proposed met…
Possibilistic Fuzzy Local Information C-Means with Automated Feature Selection for Seafloor Segmentation
Joshua Peeples, Daniel Suen, Alina Zare +1
The Possibilistic Fuzzy Local Information C-Means (PFLICM) method is presented as a technique to segment side-look synthetic aperture sonar (SAS) imagery into distinct regions of t…
RandCrowns: A Quantitative Metric for Imprecisely Labeled Tree Crown Delineation
Dylan Stewart, Alina Zare, Sergio Marconi +5
Supervised methods for object delineation in remote sensing require labeled ground-truth data. Gathering sufficient high quality ground-truth data is difficult, especially when tar…
Complex Scene Classification of PolSAR Imagery based on a Self-paced Learning Approach
Wenshuai Chen, Shuiping Gou, Xinlin Wang +3
Existing polarimetric synthetic aperture radar (PolSAR) image classification methods cannot achieve satisfactory performance on complex scenes characterized by several types of lan…
Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty
Xiaoxiao Du, Alina Zare
In remote sensing, each sensor can provide complementary or reinforcing information. It is valuable to fuse outputs from multiple sensors to boost overall performance. Previous sup…
Multiple Instance Choquet Integral Classifier Fusion and Regression for Remote Sensing Applications
Xiaoxiao Du, Alina Zare
In classifier (or regression) fusion the aim is to combine the outputs of several algorithms to boost overall performance. Standard supervised fusion algorithms often require accur…
Multiple Instance Hybrid Estimator for Hyperspectral Target Characterization and Sub-pixel Target Detection
Changzhe Jiao, Chao Chen, Ronald G. McGarvey +3
The Multiple Instance Hybrid Estimator for discriminative target characterization from imprecisely labeled hyperspectral data is presented. In many hyperspectral target detection p…
Possibilistic Fuzzy Local Information C-Means for Sonar Image Segmentation
Alina Zare, Nicholas Young, Daniel Suen +3
Side-look synthetic aperture sonar (SAS) can produce very high quality images of the sea-floor. When viewing this imagery, a human observer can often easily identify various sea-fl…
Hyperspectral Unmixing with Endmember Variability using Semi-supervised Partial Membership Latent Dirichlet Allocation
Sheng Zou, Hao Sun, Alina Zare
A semi-supervised Partial Membership Latent Dirichlet Allocation approach is developed for hyperspectral unmixing and endmember estimation while accounting for spectral variability…
Multiple Instance Hybrid Estimator for Learning Target Signatures
Changzhe Jiao, Alina Zare
Signature-based detectors for hyperspectral target detection rely on knowing the specific target signature in advance. However, target signature are often difficult or impossible t…
Map-guided Hyperspectral Image Superpixel Segmentation Using Proportion Maps
Hao Sun, Alina Zare
A map-guided superpixel segmentation method for hyperspectral imagery is developed and introduced. The proposed approach develops a hyperspectral-appropriate version of the SLIC su…
Partial Membership Latent Dirichlet Allocation
Chao Chen, Alina Zare, Huy Trinh +3
Topic models (e.g., pLSA, LDA, sLDA) have been widely used for segmenting imagery. However, these models are confined to crisp segmentation, forcing a visual word (i.e., an image p…
Hyperspectral Unmixing with Endmember Variability using Partial Membership Latent Dirichlet Allocation
Sheng Zou, Alina Zare
The application of Partial Membership Latent Dirichlet Allocation(PM-LDA) for hyperspectral endmember estimation and spectral unmixing is presented. PM-LDA provides a model for a h…
Multiple Instance Hyperspectral Target Characterization
Alina Zare, Changzhe Jiao, Taylor Glenn
In this paper, two methods for multiple instance target characterization, MI-SMF and MI-ACE, are presented. MI-SMF and MI-ACE estimate a discriminative target signature from imprec…
Heart Beat Characterization from Ballistocardiogram Signals using Extended Functions of Multiple Instances
Changzhe Jiao, Princess Lyons, Alina Zare +2
A multiple instance learning (MIL) method, extended Function of Multiple Instances (FUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The…
Instance Influence Estimation for Hyperspectral Target Signature Characterization using Extended Functions of Multiple Instances
Sheng Zou, Alina Zare
The Extended Functions of Multiple Instances (eFUMI) algorithm is a generalization of Multiple Instance Learning (MIL). In eFUMI, only bag level (i.e. set level) labels are needed…
Buried object detection using handheld WEMI with task-driven extended functions of multiple instances
Matthew Cook, Alina Zare, Dominic Ho
Many effective supervised discriminative dictionary learning methods have been developed in the literature. However, when training these algorithms, precise ground-truth of the tra…
Adaptive coherence estimator (ACE) for explosive hazard detection using wideband electromagnetic induction (WEMI)
Brendan Alvey, Alina Zare, Matthew Cook +1
The adaptive coherence estimator (ACE) estimates the squared cosine of the angle between a known target vector and a sample vector in a whitened coordinate space. The space is whit…
Multiple Instance Dictionary Learning using Functions of Multiple Instances
Changzhe Jiao, Alina Zare
A multiple instance dictionary learning method using functions of multiple instances (DL-FUMI) is proposed to address target detection and two-class classification problems with in…
Estimating Target Signatures with Diverse Density
Taylor Glenn, Alina Zare
Hyperspectral target detection algorithms rely on knowing the desired target signature in advance. However, obtaining an effective target signature can be difficult; signatures obt…