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Found 5 papers, 1 papers with code
Foundation Models for Generalist Geospatial Artificial Intelligence
This paper introduces a first-of-a-kind framework for the efficient pre-training and fine-tuning of foundational models on extensive geospatial data.
Toward Foundation Models for Earth Monitoring: Generalizable Deep Learning Models for Natural Hazard Segmentation
However, DL-based approaches are designed for one specific task in a single geographic region based on specific frequency bands of satellite data.
A reconfigurable integrated electronic tongue and its use in accelerated analysis of juices and wines
Potentiometric electronic tongues (ETs) leveraging trends in miniaturization and internet of things (IoT) bear promise for facile mobile chemical analysis of complex multicomponent liquids, such as beverages.
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data
Using computational models, we find that language and multimodal representations of mobile typed text (spanning typed characters, words, keystroke timings, and app usage) are predictive of daily mood.
Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study
Mental health conditions remain under-diagnosed even in countries with common access to advanced medical care.
