11 citations · 24 across the 19 of their papers we have counts for
4 papers · 1 filter
A Vision-Language Model (VLM)-based Pipeline for End-to-End Procedural Modeling of Field-Grown Maize from Point Clouds
Mozhgan Hadadi, Talukder Z. Jubery, Adarsh Krishnamurthy +1
Editable 3D models of field-grown crops support high-throughput phenotyping and in silico breeding trials, but building them from scanned point clouds requires organ-level segmenta…
Automated Maize Ear Phenotyping Using 3D Reconstructions
Ritwesh A. Kumar, Som Tripathi, Peja Matthews +5
Maize kernel traits such as row number, kernels per row, and kernel size vary largely for genetic reasons and are consistently associated with regions of the genome that influence…
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…
HS-3D-NeRF: 3D Surface and Hyperspectral Reconstruction From Stationary Hyperspectral Images Using Multi-Channel NeRFs
Kibon Ku, Talukder Z. Jubery, Adarsh Krishnamurthy +1
Advances in hyperspectral imaging (HSI) and 3D reconstruction have enabled accurate, high-throughput characterization of agricultural produce quality and plant phenotypes, both ess…