Sruti Das Choudhury

University of Nebraska–Lincoln — United States

Agricultural and Biological Sciences · Life Sciences

14h-index751citations41works5.82yr avg
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Research Topics

Smart Agriculture and AI(23), Remote Sensing in Agriculture(16), Leaf Properties and Growth Measurement(11), Genomics and Phylogenetic Studies(5), Genetics and Plant Breeding(4)

Publications41 total

Unidimensional Phenotypes using Concurrent Imaging Collected Via a High-Throughput Imaging System
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
Programming‐Assisted Imaging of Cellular Nitric Oxide Efflux Gradients and Directionality via Carbon Nanotube Sensors
Small Science·2025· 2 citedOpen Access
Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning
Frontiers in Plant Science·2024· 2 citedOpen Access
A Machine Learning-Based Probabilistic Approach for Irrigation Scheduling
Water Resources Management·2024· 13 cited
Current challenges and future of agricultural genomes to phenomes in the USA
Genome biology·2024· 18 citedOpen Access
CottonHusker: Deep Learning Enabled Cotton Picking Robot for Smart Agriculture
2024
Current Challenges and Future of Agricultural Genomes to Phenomes in the U.S.
2023Open Access
An ML-based Probabilistic Approach for Irrigation Scheduling
2023· 1 citedOpen Access
Drought stress prediction and propagation using time series modeling on multimodal plant image sequences
Frontiers in Plant Science·2023· 12 citedOpen Access
EmergeNet: A novel deep-learning based ensemble segmentation model for emergence timing detection of coleoptile
Frontiers in Plant Science·2023· 5 citedOpen Access
From Laboratory to Field: Unsupervised Domain Adaptation for Plant Disease Recognition in the Wild
Plant Phenomics·2023· 51 citedOpen Access
FlowerPhenoNet: Automated Flower Detection from Multi-View Image Sequences Using Deep Neural Networks for Temporal Plant Phenotyping Analysis
Remote Sensing·2022· 16 citedOpen Access
Time Series Modeling for Drought Stress Propagation in Plants using Hyperspectral Imagery
2022· 1 citedOpen Access
FlowerPhenoNet: Automated Flower Detection from Multi-view Image Sequences using Deep Neural Networks for Temporal Plant Phenotyping Analysis
Preprints.org·2022· 2 citedOpen Access
Cosegmentation for Plant Phenotyping+ (CosegPP+) Data Repository Collected Via a High-Throughput Imaging System
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
Cosegmentation for Plant Phenotyping+ (CosegPP+) Data Repository Collected Via a High-Throughput Imaging System
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
Single-Aspect Phenotypes for Modality, Perspective, and Time Collected Via a High-Throughput Imaging System
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
A Segmentation-Guided Deep Learning Framework for Leaf Counting
Frontiers in Plant Science·2022· 42 citedOpen Access
Accurate Co-Segmentation in High-Throughput And High Dimensional Plant Image Sequences
2022Open Access
Accurate Co-Segmentation in High-Throughput And High Dimensional Plant Image Sequences
2022Open Access
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Frequent Co-authors

Ashok Samal(20), Tala Awada(11), Rubi Quiñones(11), Francisco Muñoz‐Arriola(11), Xijian Fan(4), Anastasios Mazis(4), Tardi Tjahjadi(4), Srinidhi Bashyam(3), Carmela R. Guadagno(3), Aankit Das(3), Qiaolin Ye(2), Vincent Stoerger(2), Saptarsi Goswami(2), Diego Jarquín(2), Réka Howard(2), Alencar Xavier(2), Christopher K. Tuggle(2), Jennifer Clarke(2), Brenda M. Murdoch(2), Eric Lyons(2)