10 papers
SAGE: Scalable Agentic Grounded Evaluation for Crop Disease Diagnosis
Muhammad Arbab Arshad, Tirtho Roy, Yanben Shen +7
Plant disease diagnosis is critical for food security, yet training disease-recognition models that generalize across crops, pathogens, and field conditions remains challenging bec…
ReinDSplit: Reinforced Dynamic Split Learning for Pest Recognition in Precision Agriculture
Vishesh Kumar Tanwar, Soumik Sarkar, Asheesh K. Singh +1
To empower precision agriculture through distributed machine learning (DML), split learning (SL) has emerged as a promising paradigm, partitioning deep neural networks (DNNs) betwe…
TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models
Shivani Chiranjeevi, Hossein Zaremehrjerdi, Zi K. Deng +9
The rapid global loss of biodiversity, particularly among insects, represents an urgent ecological crisis. Current methods for insect species discovery are manual, slow, and severe…
Towards Large Reasoning Models for Agriculture
Hossein Zaremehrjerdi, Shreyan Ganguly, Ashlyn Rairdin +17
Agricultural decision-making involves complex, context-specific reasoning, where choices about crops, practices, and interventions depend heavily on geographic, climatic, and econo…
WeedNet: A Foundation Model-Based Global-to-Local AI Approach for Real-Time Weed Species Identification and Classification
Yanben Shen, Timilehin T. Ayanlade, Venkata Naresh Boddepalli +13
Early weed identification is crucial for effective management and control, and researchers, agronomists, and technology developers are increasingly interested in automating this pr…
Optimizing Navigation And Chemical Application in Precision Agriculture With Deep Reinforcement Learning And Conditional Action Tree
Mahsa Khosravi, Zhanhong Jiang, Joshua R Waite +6
This paper presents a novel reinforcement learning (RL)-based planning scheme for optimized robotic management of biotic stresses in precision agriculture. The framework employs a…