activity
20232026
most citedAgri-GNN: A Novel Genotypic-Topological Graph Neural Network Framework Built on GraphSAGE for Optimized Yield Prediction

8 citations · 18 across the 12 of their papers we have counts for

collaborators

13 papers

cs.CV2026

Agronomic Characterization and Time-Series UAV Phenotyping to Support Field Pea Breeding in Iowa

Yanben Shen, Joscif Raigne, Asheesh Singh +1

Field pea has gained interest in the Midwest U.S. and has the potential to benefit Iowa cropping systems. This study evaluated 17 accessions and 7 Canadian varieties for agronomic…

cs.MA2026

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…

cs.LG2025

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…

cs.CV2025

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…

cs.LG2025★ 1 cited

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…

cs.CV2025

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…

cs.CV2024

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…

cs.AI2024★ 2 cited

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…

cs.LG2024★ 3 cited

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…

cs.CV2024

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…

cs.CV2024★ 2 cited

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…

cs.CY2023★ 2 cited

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…

cs.LG2023★ 8 cited

Agri-GNN: A Novel Genotypic-Topological Graph Neural Network Framework Built on GraphSAGE for Optimized Yield Prediction

Aditya Gupta, Asheesh Singh

Agriculture, as the cornerstone of human civilization, constantly seeks to integrate technology for enhanced productivity and sustainability. This paper introduces $\textit{Agri-GN…