Results 211 to 220 of about 22,677 (288)

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

Functions and Sensors of Smart Walkers From 2015 to 2024: Scoping Review. [PDF]

JMIR Rehabil Assist Technol
Strutz N, Brodowski H, Schulze S.
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

WeatherMamba: Reliable Geometry-Aware Generalization for Adverse-Weather LiDAR Sensor Point-Cloud Semantic Segmentation. [PDF]

Sensors (Basel)
Huang H, Zhang X, Zhang Y, Yang J.
europepmc   +1 more source

Unmanned aerial vehicle–based spatiotemporal phenotyping and growth modeling for forecasting potato yield

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Monitoring spatial variations in plant growth and forecasting yield before harvest provides valuable insights for optimizing agronomic decision‐making in potato (Solanum tuberosum L.) cultivation. Although unmanned aerial vehicle (UAV)‐based remote sensing has recently enabled the development of tuber fresh weight (TW) estimation models, their
Yuto Imachi, Kunihiro Tanaka, Minato Miyauchi, Kyosuke Miyamoto, Masahiro Okada, Pieter M. Blok, Wei Guo, Hiroyoshi Iwata   +7 more
wiley   +1 more source

Risk-Aware Fault-Tolerant Multisensor Fusion for Human-Machine Decision Support in Autonomous Navigation and Mooring in Confined Waters. [PDF]

Sensors (Basel)
Kondratyev SI, Khekert EV, Martyushev NV, Malozyomov BV, Kukartsev VV, Tynchenko VV, Panfilova TA, Tynchenko YA, Kozhukhova NI.   +8 more
europepmc   +1 more source

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

The 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, Valerio Hoyos‐Villegas   +1 more
wiley   +1 more source

Multimodal Sensor Fusion in Autonomous Vehicles: Technologies, Architectures, and Open Challenges. [PDF]

Sensors (Basel)
Viktor P, Kiss G.
europepmc   +1 more source

Time course sensor‐based phenotyping can predict Ascochyta blight disease severity in Cicer species

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Ascochyta blight is a widely occurring chickpea fungal disease that can cause severe yield loss. Breeding for crop resistance benefits from high‐throughput evaluation of plant–pathogen interactions in genotypes which can serve as sources of resistance.
Florian Tanner, Judith Atieno, Sara Blake, Marzena Krysinska‐Kaczmarek, Chris Brien, Mohsen Khani, Kenneth Clarke, Darren Plett, Jennifer Davidson, Bettina Berger   +9 more
wiley   +1 more source

Perception and Localization Error Propagation and Robust Path-Tracking Control for Agricultural Machinery in Hilly Orchards: A Review. [PDF]

Sensors (Basel)
Zhang Z, Wang Y, Lei H, Dong X, Jia W.
europepmc   +1 more source