Abstract: Computer vision has rapidly evolved into a transformative technology, enabling machines to interpret and analyze visual data with unprecedented accuracy. Beyond its traditional applications in industry and commerce, computer vision is now being harnessed to address pressing challenges in scientific and societal domains such as archaeology, agriculture, and wildlife conservation.
In this talk, Dr. Saket Anand and Prof. Ilan Shimshoni from the University of Haifa will explore how computer vision techniques are being applied across these diverse fields. The session will highlight how automated image analysis, pattern recognition, and deep learning models can uncover insights that were previously inaccessible, while also emphasizing the interdisciplinary nature of these applications.
Key themes will include:
Archaeology: Using computer vision to analyze artifacts, reconstruct ancient sites, and preserve cultural heritage.
Agriculture: Leveraging vision-based systems for crop monitoring, disease detection, and yield optimization.
Wildlife: Applying visual recognition to track species, monitor habitats, and support conservation efforts.
Challenges of deploying computer vision in real-world, resource-constrained environments.
Future directions for integrating vision systems with other AI technologies to expand impact.
The presentation will showcase case studies and ongoing research, demonstrating how computer vision is bridging technology with human knowledge to advance discovery, sustainability, and conservation. By extending its reach into archaeology, agriculture, and wildlife, computer vision is proving to be a powerful tool for both scientific inquiry and societal benefit.