3 citations · 12 across the 16 of their papers we have counts for
17 papers
AI-integrated models for assessing agricultural resilience
Joshua R. Waite, Dana Golden, Brett Indelicato +8
Agricultural supply chains are vulnerable to disruptions through linked biophysical and economic systems. We develop an AI-powered tool that integrates economic models (GTAP) with…
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…
Crossmodal learning for Crop Canopy Trait Estimation
Timilehin T. Ayanlade, Anirudha Powadi, Talukder Z. Jubery +2
Recent advances in plant phenotyping have driven widespread adoption of multi sensor platforms for collecting crop canopy reflectance data. This includes the collection of heteroge…
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…
STITCH: Surface reconstrucTion using Implicit neural representations with Topology Constraints and persistent Homology
Anushrut Jignasu, Ethan Herron, Zhanhong Jiang +5
We present STITCH, a novel approach for neural implicit surface reconstruction of a sparse and irregularly spaced point cloud while enforcing topological constraints (such as havin…
Geometry Matters: Benchmarking Scientific ML Approaches for Flow Prediction around Complex Geometries
Ali Rabeh, Ethan Herron, Aditya Balu +4
Rapid and accurate simulations of fluid dynamics around complicated geometric bodies are critical in a variety of engineering and scientific applications, including aerodynamics an…
Soybean Maturity Prediction using 2D Contour Plots from Drone based Time Series Imagery
Bitgoeul Kim, Samuel W. Blair, Talukder Z. Jubery +4
Plant breeding programs require assessments of days to maturity for accurate selection and placement of entries in appropriate tests. In the early stages of the breeding pipeline,…
Robust soybean seed yield estimation using high-throughput ground robot videos
Jiale Feng, Samuel W. Blair, Timilehin Ayanlade +5
We present a novel method for soybean (Glycine max (L.) Merr.) yield estimation leveraging high throughput seed counting via computer vision and deep learning techniques. Tradition…
AgGym: An agricultural biotic stress simulation environment for ultra-precision management planning
Mahsa Khosravi, Matthew Carroll, Kai Liang Tan +8
Agricultural production requires careful management of inputs such as fungicides, insecticides, and herbicides to ensure a successful crop that is high-yielding, profitable, and of…
Leveraging Vision Language Models for Specialized Agricultural Tasks
Muhammad Arbab Arshad, Talukder Zaki Jubery, Tirtho Roy +8
As Vision Language Models (VLMs) become increasingly accessible to farmers and agricultural experts, there is a growing need to evaluate their potential in specialized tasks. We pr…
Class-specific Data Augmentation for Plant Stress Classification
Nasla Saleem, Aditya Balu, Talukder Zaki Jubery +4
Data augmentation is a powerful tool for improving deep learning-based image classifiers for plant stress identification and classification. However, selecting an effective set of…
BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity
Chih-Hsuan Yang, Benjamin Feuer, Zaki Jubery +12
We introduce BioTrove, the largest publicly accessible dataset designed to advance AI applications in biodiversity. Curated from the iNaturalist platform and vetted to include only…
Multi-Sensor and Multi-temporal High-Throughput Phenotyping for Monitoring and Early Detection of Water-Limiting Stress in Soybean
Sarah E. Jones, Timilehin Ayanlade, Benjamin Fallen +5
Soybean production is susceptible to biotic and abiotic stresses, exacerbated by extreme weather events. Water limiting stress, i.e. drought, emerges as a significant risk for soyb…
Smart Connected Farms and Networked Farmers to Tackle Climate Challenges Impacting Agricultural Production
Behzad J. Balabaygloo, Barituka Bekee, Samuel W. Blair +18
To meet the grand challenges of agricultural production including climate change impacts on crop production, a tight integration of social science, technology and agriculture exper…