Results 111 to 120 of about 3,522,681 (315)

INFORMATION EXTRACTION IN TOMB PIT USING HYPERSPECTRAL DATA [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics.
X. Yang, M. Hou, M. Hou, S. Lyu, S. Lyu, S. Ma, Z. Gao, S. Bai, M. Gu, Y. Liu   +9 more
doaj   +1 more source

An Integrated Framework Coupling Hierarchical Hyperspectral i‐trait Screening, Gene Identification, and Functional Validation for Genetic Dissection of Salt Tolerance in Cotton

Advanced Science, EarlyView.
An integrated phenomics–genomics framework captures dynamic salt‐stress responses in laboratory‐grown cotton seedlings through time‐series hyperspectral imaging and non‐destructive i‐trait extraction. Hierarchical screening identifies biologically relevant, heritable, and non‐redundant traits for high‐resolution GWAS, identifying GhST7.
Bowei Xu, Le Liu, Mengli Yu, Yuling Guo, Junli Ye, Jun Zhang, Rumeng Zhao, Jiajie Yang, Wanneng Yang, Yameng Xu, Liqiang Fan, Zuoren Yang   +11 more
wiley   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

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

Inverting the Concentrations of Chlorophyll-a and Chemical Oxygen Demand in Urban River Networks Using Normalized Hyperspectral Data

Sensors
Chlorophyll-a (Chl-a) and chemical oxygen demand (COD) are key indicators for water quality evaluation. In previous research on the inversion of Chl-a and COD concentrations using hyperspectral data, disparities in hyperspectral data types have ...
Rongda Guan, Yingzhuo Hou, Maham Arif, Qianguo Xing   +3 more
doaj   +1 more source

Discovering coherency of specific gene expression and optical reflectance properties of barley genotypes differing for resistance reactions against powdery mildew.

PLoS ONE, 2019
Hyperspectral imaging has proved its potential for evaluating complex plant-pathogen interactions. However, a closer link of the spectral signatures and genotypic characteristics remains elusive.
Matheus Thomas Kuska, Jan Behmann, Mahsa Namini, Erich-Christian Oerke, Ulrike Steiner, Anne-Katrin Mahlein   +5 more
doaj   +1 more source

Hyperspectral reflectance in grassland plots undergoing different fertilization regimes in Central Portugal from March to June 2016

, 2018
Hyperspectral reflectance in grassland plots undergoing different fertilization regimes in Central Portugal from March to June ...
Sofia Cerasoli (5574044), Cerasoli, Sofia, Joana Faria (493162), Campagnolo, Manuel, Caldeira, Maria Conceição, Maria Conceição Caldeira (6976007), Faria, Joana, Manuel Campagnolo (6976001), Nogueira, Carla, Carla Nogueira (6976004)   +9 more
core   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Remote sensing reflectance reconstruction to obtain water optical properties from MERIS multispectral satellite images [PDF]

, 2010
We use a multiple regression analysis and a data bank of about 400 reflectance spectra to reconstruct hyperspectral reflectances between 400 and 900 nm with a 5 nm step using only the values known at the wavelengths of the MERIS sensor level 2 data.
Frédéric Jourdin, Schmeltz, Marjorie, Jourdin, Frédéric, Gege, Peter, Froidefond, Jean-Marie, Marjorie Schmeltz, Peter Gege, Jean-Marie Froidefond   +7 more
core   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source