77 citations · 91 across the 18 of their papers we have counts for
11 papers · 1 filter
Artifact Removal and Image Restoration in AFM:A Structured Mask-Guided Directional Inpainting Approach
Juntao Zhang, Angona Biswas, Jaydeep Rade +5
Atomic Force Microscopy (AFM) enables high-resolution surface imaging at the nanoscale, yet the output is often degraded by artifacts introduced by environmental noise, scanning im…
In-Context Adaptation of VLMs for Few-Shot Cell Detection in Optical Microscopy
Shreyan Ganguly, Angona Biswas, Jaydeep Rade +9
Foundation vision-language models (VLMs) excel on natural images, but their utility for biomedical microscopy remains underexplored. In this paper, we investigate how in-context le…
SC-NeRF: NeRF-based Point Cloud Reconstruction using a Stationary Camera for Agricultural Applications
Kibon Ku, Talukder Z Jubery, Elijah Rodriguez +4
This paper presents a NeRF-based framework for point cloud (PCD) reconstruction, specifically designed for indoor high-throughput plant phenotyping facilities. Traditional NeRF-bas…
Accessing the Effect of Phyllotaxy and Planting Density on Light Use Efficiency in Field-Grown Maize using 3D Reconstructions
Nasla Saleem, Talukder Zaki Jubery, Aditya Balu +5
High-density planting is a widely adopted strategy to enhance maize productivity, yet it introduces challenges such as increased interplant competition and shading, which can limit…
FUSE: First-Order and Second-Order Unified SynthEsis in Stochastic Optimization
Zhanhong Jiang, Md Zahid Hasan, Aditya Balu +3
Stochastic optimization methods have actively been playing a critical role in modern machine learning algorithms to deliver decent performance. While numerous works have proposed a…
MaizeField3D: A Curated 3D Point Cloud and Procedural Model Dataset of Field-Grown Maize from a Diversity Panel
Elvis Kimara, Mozhgan Hadadi, Jackson Godbersen +6
The development of artificial intelligence (AI) and machine learning (ML) based tools for 3D phenotyping, especially for maize, has been limited due to the lack of large and divers…