Results 191 to 200 of about 2,942 (257)

Pixel‐level supervision resolves overlap: Benchmarking YOLOv12 segmentation for accurate multi‐cluster dry bean stand counting from time series unoccupied aerial systems imagery

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract An agronomic trait such as stand count is important for cultivar development and crop management practices. Manually counting the number of plants is time consuming, labor‐intensive, and prone to error. The use of unoccupied aerial systems (UAS)‐collected red, green, blue (RGB) imagery in conjunction with advanced deep learning and image ...
Aliasghar Bazrafkan   +1 more
wiley   +1 more source

Bayesian optimized color filter: A fast method for segmentation of plant phenotypes from 3D point cloud images

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer   +6 more
wiley   +1 more source

Genomic and phenomic prediction models improve selection accuracy for complex traits in alfalfa

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Predictive breeding has been proposed as an effective approach to accelerate genetic gain for complex traits. Genomic prediction (GP) models have been developed in alfalfa (Medicago sativa L.) for key traits in the last decade. More recently, phenomic prediction (PP) models have been proposed as a low‐cost, high‐throughput alternative to GP in
Pablo Sipowicz   +8 more
wiley   +1 more source

Close-Range 3D Hyperspectral Measurement System with a Physics-Guided Spectral Correction Model. [PDF]

open access: yesSensors (Basel)
Liu Z   +8 more
europepmc   +1 more source

Dual‐Branch Network With Enhanced Feature Fusion for Improved Rice Classification Accuracy

open access: yesJournal of Sustainable Agriculture and Environment, Volume 5, Issue 4, December 2026.
ABSTRACT Accurate mapping of rice, one of the world's most important food crops, is critical for monitoring its growth, estimating yields, and supporting global food security. Most deep learning methods for crop classification rely on multi‐temporal optical remote sensing data. However, it is difficult to obtain sufficient ground‐truth samples for time‐
Rongfei Ma   +6 more
wiley   +1 more source

IR-Action Spectroscopy of the Astrochemically Relevant HCCS<sup>+</sup> Cation. [PDF]

open access: yesACS Earth Space Chem
Michielan M   +9 more
europepmc   +1 more source

AI‐Powered Surveillance Systems: A Comprehensive Review of Technologies, Applications, Challenges, and Deployment Considerations

open access: yesWIREs Data Mining and Knowledge Discovery, Volume 16, Issue 4, December 2026.
Overview of AI‐powered surveillance technologies, applications, challenges, limitations, and deployment considerations. ABSTRACT Artificial intelligence (AI) has rapidly transformed smart surveillance systems, significantly leveraging technologies such as deep learning, computer vision, and adaptive monitoring.
Tanzila Kehkashan   +7 more
wiley   +1 more source

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