12 citations · 19 across the 6 of their papers we have counts for
9 papers
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…
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…
Investigation of Initialization Strategies for the Multiple Instance Adaptive Cosine Estimator
James Bocinsky, Connor McCurley, Daniel Shats +1
Sensors which use electromagnetic induction (EMI) to excite a response in conducting bodies have long been investigated for subsurface explosive hazard detection. In particular, EM…
Comparison of Hand-held WEMI Target Detection Algorithms
Connor H. McCurley, James Bocinsky, Alina Zare
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 lo…
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…