Results 41 to 50 of about 4,471 (236)
Hyperspectral Band Selection Method Based on Global Partition Clustering
Band selection is an important step in the dimensionality reduction processing of hyperspectral images and is highly important for eliminating redundant spectral information and reducing computational costs.
Tingrui Hu, Xian Guo, Peichao Gao
doaj +1 more source
A MEMS‐integrated metamaterial filter enables continuous, low‐voltage spectral tuning in the long‐wavelength infrared (LWIR). The device employs extraordinary optical transmission in a dual suspended metasurface stack, where electrostatic actuation precisely controls the intermembrane air gap.
Oleg Bannik +6 more
wiley +1 more source
Micromachined Double‐Membrane Mechanically Tunable Metamaterial for Thermal Infrared Filtering
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 +7 more
wiley +1 more source
Mid‐infrared photothermal imaging enables multidimensional profiling of micro‐ and nanoplastics in bottled water. A total of 9.9 × 104 particles L−1 is detected, with 64% in the nanoscale regime. Spectral evolution, including peak narrowing and band shifts, reveals local chain reorganization in polyethylene terephthalate (PET), highlighting intrinsic ...
Xinyu Deng +4 more
wiley +1 more source
Incorporating band selection in the spatial selection of spectral endmembers
The impact of band selection on endmember selection is seldom explored in the analysis of hyperspectral imagery. This study incorporates the N-dimensional Spectral Solid Angle (NSSA) band selection tool into the Spectral-Spatial Endmember Extraction ...
Yaqian Long, Benoit Rivard, Derek Rogge
doaj +1 more source
Silicon hot‐carrier photodetectors offer a CMOS‐compatible pathway for SWIR detection but suffer from intrinsically low quantum efficiency. Here, we introduce a quasi‐generalized antireflection coating (QARC) that universally enhances optical absorption and quantum efficiency, enabling the first CMOS‐compatible SWIR imaging with silicon hot‐carrier ...
Eui‐Hyoun Ryu +11 more
wiley +1 more source
Segmented Autoencoders for Unsupervised Embedded Hyperspectral Band Selection [PDF]
One of the major challenges in hyperspectral imaging (HSI) is the selection of the most informative wavelengths within the vast amount of data in a hypercube. Band selection can reduce the amount of data and computational cost as well as counteracting the negative effects of redundant and erroneous information. In this paper, we propose an unsupervised,
Tschannerl, Julius +3 more
openaire +2 more sources
Advancing Fruit Bioimpedance Monitoring With Sustainable, Soft, And Bio‐Based Electrodes Beyond ECG
Electrical impedance spectroscopy enables non‐destructive fruit quality monitoring, but conventional ECG and needle electrodes compromise signal stability, fruit physiology, and sustainability. This perspective highlights the transition toward soft, biocompatible, and biodegradable electrode interfaces based on natural substrates, bio‐derived ...
Sundus Riaz +6 more
wiley +1 more source
Hyperspectral Image Visualization Using Band Selection
This paper investigates hyperspectral image display based on selection of three spectral channels to build a red-green-blue (RGB) composite. A series of band selection algorithms are implemented and compared for this purpose. In particular, three color composition schemes based on visualization-oriented spectral segmentations are proposed.
Hongjun Su, Qian Du 0001, Peijun Du
openaire +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source

