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Results for "constraint satisfaction"

Modeling Complex Object Changes in Satellite Image Time-Series: Approach based on CSP and Spatiotemporal Graph

arXiv · May 24

This paper introduces a novel approach for monitoring and analyzing the evolution of complex geographic objects in satellite image time-series. The method uses a spatiotemporal graph and constraint satisfaction problems (CSP) to model and analyze object changes. Experiments on real-world satellite images from Saudi Arabian cities demonstrate the effectiveness of the proposed approach.

Neural Models with Symbolic Representations for Perceptuo-Reasoning Tasks

MBZUAI · Invalid Date

Mausam, head of Yardi School of AI at IIT Delhi and affiliate professor at University of Washington, will discuss Neuro-Symbolic AI. The talk will cover recent research threads with applications in NLP, probabilistic decision-making, and constraint satisfaction. Mausam's research explores neuro-symbolic machine learning, computer vision for radiology, NLP for robotics, multilingual NLP, and intelligent information systems. Why it matters: Neuro-Symbolic AI is gaining importance as it combines the strengths of neural and symbolic approaches, potentially leading to more robust and explainable AI systems.