most citedDeep learning powered real-time identification of insects using citizen science data

11 citations · 14 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

AI-enabled Low-Cost 3D Maize Ear Morphometry Platform at Breeding Scale

Therin Young, Elijah Rodriguez, Lisa Coffey +4

Maize ear geometry (length, width, curvature, and volume) is closely tied to yield and grain-filling outcomes, but existing high-throughput phenotyping pipelines remain constrained…

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.LG2024

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…

cs.CV202311 cited

Deep learning powered real-time identification of insects using citizen science data

Shivani Chiranjeevi, Mojdeh Sadaati, Zi K Deng +10

Insect-pests significantly impact global agricultural productivity and quality. Effective management involves identifying the full insect community, including beneficial insects an…

cs.CV20233 cited

Out-of-distribution detection algorithms for robust insect classification

Mojdeh Saadati, Aditya Balu, Shivani Chiranjeevi +5

Deep learning-based approaches have produced models with good insect classification accuracy; Most of these models are conducive for application in controlled environmental conditi…