1 citations · 1 across the 5 of their papers we have counts for
5 papers
ELMZip: Onboard Satellite Image Compression via Extreme Learning Machines for Efficient Downlink
Woojin Cho, Junghwan Park, Sangcheol Sim +3
The acquisition of multispectral imagery via small satellites (e.g., CubeSats) presents significant data downlink challenges due to high data volumes and restricted communication w…
Fourier-Modulated Implicit Neural Representation for Multispectral Satellite Image Compression
Woojin Cho, Steve Andreas Immanuel, Junhyuk Heo +1
Multispectral satellite images play a vital role in agriculture, fisheries, and environmental monitoring. However, their high dimensionality, large data volumes, and diverse spatia…
Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model
Steve Andreas Immanuel, Woojin Cho, Junhyuk Heo +1
Limited data is a common problem in remote sensing due to the high cost of obtaining annotated samples. In the few-shot segmentation task, models are typically trained on base clas…
Building Age Estimation: A New Multi-Modal Benchmark Dataset and Community Challenge
Nikolaos Dionelis, Alessandra Feliciotti, Mattia Marconcini +8
Estimating the construction year of buildings is critical for advancing sustainability, as older structures often lack energy-efficient features. Sustainable urban planning relies…
Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain
Steve Andreas Immanuel, Hagai Raja Sinulingga
Few-shot segmentation is a task to segment objects or regions of novel classes within an image given only a few annotated examples. In the generalized setting, the task extends to…