The Conference convenes experts working in foundational AI, computer vision, machine learning, data analytics, and sustainability science. The track emphasizes how these complementary, multi-disciplinary approaches collectively generate richer, more actionable insights into farm management, crop health, and environmental stewardship. We invite submissions that explore a wide range of research, including but not limited to:
Foundational AI for Agriculture:
– Generative AI
– Foundation Models
– Multimodal Learning
– Self-Supervised and Few-Shot Learning
Computer Vision and Image Processing:
– 3D Vision for Agriculture
– Semantic and Instance Segmentation
– Scene Understanding and Analysis
Machine Learning for Crop Management:
– Predictive Modeling and Forecasting
– Reinforcement Learning for Control
Advanced Agricultural Systems:
– Agentic AI and Autonomous Systems
– Digital Twins and Simulation
– Neurosymbolic AI
Trustworthy and Responsible AI in Agriculture:
– Interpretability and Explainability (XAI)
– Robustness and Uncertainty Quantification
– Fairness, Ethics, and Policy