42 citations · 338 across the 135 of their papers we have counts for
11 papers · 1 filter
Do Satellite Tasks Need Special Pretraining?
Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan +4
Foundation models have advanced machine learning across various modalities, including images. Recently multiple teams trained foundation models specialized for remote sensing appli…
Residual-based Language Models are Free Boosters for Biomedical Imaging
Zhixin Lai, Jing Wu, Suiyao Chen +2
In this study, we uncover the unexpected efficacy of residual-based large language models (LLMs) as part of encoders for biomedical imaging tasks, a domain traditionally devoid of…
GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing
Jing Wu, Naira Hovakimyan, Jennifer Hobbs
Classifying and segmenting patterns from a limited number of examples is a significant challenge in remote sensing and earth observation due to the difficulty in acquiring accurate…
Hallucination Improves the Performance of Unsupervised Visual Representation Learning
Jing Wu, Jennifer Hobbs, Naira Hovakimyan
Contrastive learning models based on Siamese structure have demonstrated remarkable performance in self-supervised learning. Such a success of contrastive learning relies on two co…
Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis
Jing Wu, David Pichler, Daniel Marley +3
A key challenge for much of the machine learning work on remote sensing and earth observation data is the difficulty in acquiring large amounts of accurately labeled data. This is…
Superpixels and Graph Convolutional Neural Networks for Efficient Detection of Nutrient Deficiency Stress from Aerial Imagery
Saba Dadsetan, David Pichler, David Wilson +2
Advances in remote sensing technology have led to the capture of massive amounts of data. Increased image resolution, more frequent revisit times, and additional spectral channels…