Results 181 to 190 of about 48,380 (279)

A Structurally Optimized and Efficient Lightweight Object Detection Model for Autonomous Driving. [PDF]

Sensors (Basel)
Li M, Wang J, Chen S, Liu L, Li K, Zhao Z, Yun H.   +6 more
europepmc   +1 more source

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Image-based obstacle detection methods for the safe navigation of industrial unmanned aerial vehicles. [PDF]

Sci Rep
Wang L, Shen Y, Li H, Shi Q, Liu S, Chen S, Chen Z, Touti E.   +7 more
europepmc   +1 more source

Multiple ortho‐mosaicking software pipelines produce comparable imagery‐derived wheat phenotypes

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Unmanned aerial systems (UAS) equipped with multispectral and RGB sensors offer valuable data for monitoring crop health and assessing disease severity. However, the wide range of available photogrammetric software complicates software selection for high‐throughput plant phenotyping.
Sanju Shrestha, Phillip D. Alderman, Grishma Ojha, Brett F. Carver   +3 more
wiley   +1 more source

Rendering compact formation and trajectory tracking for cyber unmanned ground vehicles. [PDF]

Fundam Res
Zhao X, Cui Z, Chew CM, Dong F.
europepmc   +1 more source

Affordable Phenomics special topic—Foreword for The Plant Phenome Journal

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract The Affordable Phenomics special topic in The Plant Phenome Journal showcased recent advances that expand the accessibility, cost‐effectiveness, and scalability of plant phenotyping technologies. This collection of 15 articles presented innovative approaches, ranging from low‐cost sensors and open‐source analytical pipelines to artificial ...
Valerio Hoyos‐Villegas, Michael A. Gore   +1 more
wiley   +1 more source

A flexible, magnet-based miniaturized mechanical antenna enabling low-frequency cross-medium communication between unmanned systems. [PDF]

Commun Eng
Li Q, Cui Z, Ma X, Yue W, U IH, Zhou K, Qu J, Chang J, Huang Y, Liu C, Dong S, Hu Q, Cui Y, Zang X.   +13 more
europepmc   +1 more source

High‐throughput phenotyping for the prediction and quantification of flower‐related traits in sugarcane

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Sugarcane (Saccharum spp.), a C4 plant, is a vital renewable biofuel and sugar source for industries worldwide. However, synchronizing flowering between parental lines often poses challenges for breeders, hindering effective crossbreeding efforts.
Paulo H. da Silva Santos, João R. Vieira Manechini, Carlos Augusto Dias Kanthack Jr., Mauro Alexandre Xavier, Samira Domingues Carlin, Dilermando Perecin, Thiago G. Marconi, Leandro G. Marconi, Elisson Antonio da Costa Romanel, Stephen Derek Jackson, Marcos. G. A. Landell, Luciana R. Pinto   +11 more
wiley   +1 more source

Research on fault prediction and speed control system for unmanned combine harvesters based on IPSO-SVM and fuzzy logic. [PDF]

Front Plant Sci
Zhang S, Zang C, Yang Z, Tang L, Wang K, Wang A, Chen W, Song Q, Wei X.   +8 more
europepmc   +1 more source

Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe, Yazhou Sun, Sanai Li, Wenxuan Guo   +3 more
wiley   +1 more source