Results 31 to 40 of about 2,900 (227)

UAVs, Hyperspectral Remote Sensing, and Machine Learning Revolutionizing Reef Monitoring

Sensors, 2018
Recent advances in unmanned aerial system (UAS) sensed imagery, sensor quality/size, and geospatial image processing can enable UASs to rapidly and continually monitor coral reefs, to determine the type of coral and signs of coral bleaching.
Mark Parsons, Dmitry Bratanov, Kevin J. Gaston, Felipe Gonzalez   +3 more
doaj   +1 more source

Transparency Estimation of Narrow Rivers by UAV-Borne Hyperspectral Remote Sensing Imagery

IEEE Access, 2020
Urban rivers are often narrow, and general remote sensing data cannot meet the needs of water quality monitoring. In the process of monitoring of river water quality by remote sensing, the spectral and spatial dimension of satellite-borne images cannot ...
Lifei Wei, Zhou Wang, Can Huang, Yu Zhang, Zhengxiang Wang, Huiqiong Xia, Liqin Cao   +6 more
doaj   +1 more source

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data

Sensors, 2018
Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests.
Fernando Vanegas, Dmitry Bratanov, Kevin Powell, John Weiss, Felipe Gonzalez   +4 more
doaj   +1 more source

Shallow-Guided Transformer for Semantic Segmentation of Hyperspectral Remote Sensing Imagery

Remote Sensing, 2023
Convolutional neural networks (CNNs) have achieved great progress in the classification of surface objects with hyperspectral data, but due to the limitations of convolutional operations, CNNs cannot effectively interact with contextual information. Transformer succeeds in solving this problem, and thus has been widely used to classify hyperspectral ...
Yuhan Chen, Pengyuan Liu, Jiechen Zhao, Kaijian Huang, Qingyun Yan   +4 more
openaire   +2 more sources

4D‐Printed Magneto‐Plasmonic Microrobots for Programmable Spatiotemporal De‐Icing

Advanced Functional Materials, EarlyView.
A 4D‐printing strategy is introduced to achieve programmable de‐icing devices. By aligning gold–magnetite nanofillers within a photosensitive resin, the printed structures exhibit dual magnetic and plasmonic functionalities, enabling precise spatio‐temporal ice removal through thermoplasmonic effects.
Amélie Pérot, Andrea Cosola, Eléonore Aïdonidis, Jérôme Fresnais, Clément Sanchez, Philippe Belleville, Giancarlo Rizza, Marco Faustini   +7 more
wiley   +1 more source

Hyperspectral Remote Sensing of Phytoplankton Species Composition Based on Transfer Learning

Remote Sensing, 2019
Phytoplankton species composition research is key to understanding phytoplankton ecological and biogeochemical functions. Hyperspectral optical sensor technology allows us to obtain detailed information about phytoplankton species composition.
Qing Zhu, Fang Shen, Pei Shang, Yanqun Pan, Mengyu Li   +4 more
doaj   +1 more source

The Application of Hyperspectral Remote Sensing Imagery (HRSI) for Weed Detection Analysis in Rice Fields: A Review

Applied Sciences, 2022
Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and pests, resulting in yield loss. New weed detection technologies have
Nursyazyla Sulaiman, Nik Norasma Che’Ya, Muhammad Huzaifah Mohd Roslim, Abdul Shukor Juraimi, Nisfariza Mohd Noor, Wan Fazilah Fazlil Ilahi   +5 more
doaj   +1 more source

Micromachined Double‐Membrane Mechanically Tunable Metamaterial for Thermal Infrared Filtering

Advanced Photonics Research, Volume 6, Issue 5, May 2025.
Herein, a mechanically tunable double‐layer plasmonic metamaterial leveraging the extraordinary optical transmission effect observed in subwavelength arrays of openings within thin metal layers is presented. The concept is experimentally validated by integrating the proposed metamaterial structure into an electrostatic parallel‐plate actuator to create
Oleg Bannik, Fedor Kovalev, Mingkai Liu, Michal Zawierta, Dilusha Silva, Lorenzo Faraone, Mariusz Martyniuk, Ilya Shadrivov   +7 more
wiley   +1 more source

WU-Net: A Weakly-Supervised Unmixing Network for Remotely Sensed Hyperspectral Imagery [PDF]

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Recently, enormous efforts have been made to improve the performance of the linear or nonlinear mixing model for hyperspectral unmixing, yet their ability to handle spectral variability and extract physically meaningful endmembers remains limited. Based on the powerful learning ability of deep learning, we propose a weakly-supervised unmixing network ...
Hong, Danfeng, Chanussot, Jocelyn, Yokoya, Naoto, Heiden, Uta, Heldens, Wieke, Zhu, Xiao Xiang   +5 more
openaire   +2 more sources

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source