464 research outputs found
Semantically-Aware Retrieval of Oceanographic Phenomena Annotated on Satellite Images
Scientists in the marine domain process satellite images in order to extract information
that can be used for monitoring, understanding, and forecasting of marine phenomena, such as
turbidity, algal blooms and oil spills. The growing need for effective retrieval of related information
has motivated the adoption of semantically aware strategies on satellite images with different spatiotemporal and spectral characteristics. A big issue of these approaches is the lack of coincidence
between the information that can be extracted from the visual data and the interpretation that the
same data have for a user in a given situation. In this work, we bridge this semantic gap by connecting
the quantitative elements of the Earth Observation satellite images with the qualitative information,
modelling this knowledge in a marine phenomena ontology and developing a question answering
mechanism based on natural language that enables the retrieval of the most appropriate data for each
user’s needs. The main objective of the presented methodology is to realize the content-based search
of Earth Observation images related to the marine application domain on an application-specific
basis that can answer queries such as “Find oil spills that occurred this year in the Adriatic Sea”
AGI for Agriculture
Artificial General Intelligence (AGI) is poised to revolutionize a variety of
sectors, including healthcare, finance, transportation, and education. Within
healthcare, AGI is being utilized to analyze clinical medical notes, recognize
patterns in patient data, and aid in patient management. Agriculture is another
critical sector that impacts the lives of individuals worldwide. It serves as a
foundation for providing food, fiber, and fuel, yet faces several challenges,
such as climate change, soil degradation, water scarcity, and food security.
AGI has the potential to tackle these issues by enhancing crop yields, reducing
waste, and promoting sustainable farming practices. It can also help farmers
make informed decisions by leveraging real-time data, leading to more efficient
and effective farm management. This paper delves into the potential future
applications of AGI in agriculture, such as agriculture image processing,
natural language processing (NLP), robotics, knowledge graphs, and
infrastructure, and their impact on precision livestock and precision crops. By
leveraging the power of AGI, these emerging technologies can provide farmers
with actionable insights, allowing for optimized decision-making and increased
productivity. The transformative potential of AGI in agriculture is vast, and
this paper aims to highlight its potential to revolutionize the industry
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