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Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest Monitoring
Image-level regression is an important task in Earth observation, where visual domain and label shifts are a core challenge hampering generalization.
Benchmarking Individual Tree Mapping with Sub-meter Imagery
There is a rising interest in mapping trees using satellite or aerial imagery, but there is no standardized evaluation protocol for comparing and enhancing methods.
Connecting Images through Time and Sources: Introducing Low-data, Heterogeneous Instance Retrieval
Pick a training dataset, pick a backbone network for feature extraction, and voil\`a ; this usually works for a variety of use cases.
Unifying Remote Sensing Image Retrieval and Classification with Robust Fine-tuning
Advances in high resolution remote sensing image analysis are currently hampered by the difficulty of gathering enough annotated data for training deep learning methods, giving rise to a variety of small datasets and associated dataset-specific methods.
Challenging deep image descriptors for retrieval in heterogeneous iconographic collections
This article proposes to study the behavior of recent and efficient state-of-the-art deep-learning based image descriptors for content-based image retrieval, facing a panel of complex variations appearing in heterogeneous image datasets, in particular in cultural collections that may involve multi-source, multi-date and multi-view Permission to make digital
