activity
20242026
collaborators
Showing cs.CVShow all

6 papers · 1 filter

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.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.CV2025

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.CV2024

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,…

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.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…