Results 171 to 180 of about 15,264 (300)

Segment Anything Model-Based Hyperspectral Image Classification for Small Samples

Hyperspectral image classification (HSIC) represents a significant area of research within the domain of remote sensing. Given the intricate nature of hyperspectral images and the substantial volume of data they generate, it is essential to introduce ...
Changxu Yao, Bing Liu, Peipei He, Jing Han, Kaifeng Ma, Qingfeng Hu, Shiming Li   +6 more
core   +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

A multiscale transformer with spatial attention for hyperspectral image classification. [PDF]

Sci Rep
Ahmad I, Farooque G, Hadi F, Khader A, Abdelwahab Ghorashi S, Ahmed A, Alabdulkreem E.   +6 more
europepmc   +1 more source

UAV‐based RGB and multispectral vegetation indices as alternatives to light box‐derived dark green color index for turfgrass color assessment

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Traditionally, turfgrass color has been assessed through visual ratings or light box‐based digital image analysis, methods that are either subjective or labor‐intensive. In this study, we evaluated the potential of unmanned aerial vehicle (UAV)‐based multispectral and red‐green‐blue (RGB) imagery as a high‐throughput alternative for capturing ...
Ved Parkash, Phillip L. Vines, Sameer Khanal, Jing Zhang, Joann Conner, Susana R. Milla‐Lewis, Nino Brown, David Jespersen, Jodi Johnson‐Maynard, Brian M. Schwartz   +9 more
wiley   +1 more source

Nonlinear Dynamic Field Embedding: On Hyperspectral Scene Visualization

, 2012
In many areas of research, complex signals are commonly represented by high dimensional feature vectors. However, high dimensional vectors are difficult to analyze and interpret due to the curse of dimensionality.
Lunga, Dalton, Erosy, Okan
core  

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

Superpixel Random Selection Random Walk Multi-Branch Depthwise Convolutional Neural Network for Hyperspectral Image Classification. [PDF]

Sensors (Basel)
Zhang K, Jiang X, Cai Z.
europepmc   +1 more source

Drone‐based phenotyping of maize for multiple disease resistance and yield in breeding field trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Improving selection for multiple disease resistance (MDR) and yield in maize (Zea mays L.) requires high‐throughput, objective phenotyping tools, particularly under field conditions where several foliar diseases co‐occur. We evaluated drone‐based multispectral vegetation indices (VIs) for predicting resistance to northern leaf blight (NLB ...
Danilo E. Moreta, Nina Blahut, Nicholas Kaczmar, Judith M. Kolkman, Gary Bergstrom, Margaret Smith, Michael A. Gore, Rebecca Nelson   +7 more
wiley   +1 more source

HSICNet a novel deep learning architecture for hyperspectral image classification in remote sensing and environmental monitoring. [PDF]

Sci Rep
Purnachand K, Samrin R, Guttikonda JB, Kotoju R, Addepalli PS, Mohan A.   +5 more
europepmc   +1 more source

Accelerating Perovskite Solar Cell Development Through High‐Throughput Technologies: Computational Simulation, Automated Experimentation, and Intelligent Integration

Battery Energy, Volume 5, Issue 4, July 2026.
Moving beyond traditional trial‐and‐error, this review explores how integrating high‐throughput computational simulations, automated experimentation, and machine learning significantly accelerates perovskite solar cell development. By establishing intelligent, closed‐loop workflows, these synergistic technologies pave the way for fully autonomous ...
Yiming Wang, Ziwei Du, Yuhui Chen, Yicheng Qiu, Dong Yan, Bo Hou   +5 more
wiley   +1 more source