14 citations · 20 across the 5 of their papers we have counts for
5 papers
Investigating the Effect of Spatial Context on Multi-Task Sea Ice Segmentation
Behzad Vahedi, Rafael Pires de Lima, Sepideh Jalayer +3
Capturing spatial context at multiple scales is crucial for deep learning-based sea ice segmentation. However, the optimal specification of spatial context based on observation res…
Partial Label Learning with Focal Loss for Sea Ice Classification Based on Ice Charts
Behzad Vahedi, Benjamin Lucas, Farnoush Banaei-Kashani +4
Sea ice, crucial to the Arctic and Earth's climate, requires consistent monitoring and high-resolution mapping. Manual sea ice mapping, however, is time-consuming and subjective, p…
Comparison of Cross-Entropy, Dice, and Focal Loss for Sea Ice Type Segmentation
Rafael Pires de Lima, Behzad Vahedi, Morteza Karimzadeh
Up-to-date sea ice charts are crucial for safer navigation in ice-infested waters. Recently, Convolutional Neural Network (CNN) models show the potential to accelerate the generati…
Enhancing sea ice segmentation in Sentinel-1 images with atrous convolutions
Rafael Pires de Lima, Behzad Vahedi, Nick Hughes +3
Due to the growing volume of remote sensing data and the low latency required for safe marine navigation, machine learning (ML) algorithms are being developed to accelerate sea ice…
A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA
Benjamin Lucas, Behzad Vahedi, Morteza Karimzadeh
With COVID-19 affecting every country globally and changing everyday life, the ability to forecast the spread of the disease is more important than any previous epidemic. The conve…