Results 81 to 90 of about 24,881,858 (314)

On Improving the Performance of Kalman Filter in Denoising Oil Palm Hyperspectral Data

Agriculture
A common drawback of denoising methods of images is that all pixels are filtered regardless of the amount of noise affecting them individually. Since the essence of denoising is lowpass filtering, subjecting clean pixels to denoising results in blurring.
Imanurfatiehah Ibrahim, Hamzah Arof, Mohd Izzuddin Anuar, Mohamad Sofian Abu Talip   +3 more
doaj   +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

Unsupervised Machine Learning Framework for Identification of Spatial Distribution of Minerals on Mars

Remote Sensing
Planetary exploration missions have acquired a growing amount of remote sensing data, offering a reliable basis for studying the geological evolution of planetary bodies such as Mars.
Tejay Lovelock, Rohitash Chandra
doaj   +1 more source

Object-based classification of hyperspectral data using Random Forest algorithm

Geo-Spatial Information Science, 2018
This paper presents a new framework for object-based classification of high-resolution hyperspectral data. This multi-step framework is based on multi-resolution segmentation (MRS) and Random Forest classifier (RFC) algorithms.
S. Amini, Saeid Homayouni, A. Safari, A. Darvishsefat   +3 more
semanticscholar   +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

Hyperspectral Detection of Single and Combined Effects of Simulated Tree Shading and Alternaria alternata Infection on Sorghum bicolor, from Leaf to UAV-Canopy Scale

Agronomy
Agroforestry systems offer clear environmental and agronomic advantages, but their effect on plant–biotic stressor interactions remains poorly understood.
Lorenzo Pippi, Michael Alibani, Nicola Acito, Daniele Antichi, Giovanni Caruso, Marco Fontanelli, Michele Moretti, Cristina Nali, Silvia Pampana, Elisa Pellegrini, Andrea Peruzzi, Samuele Risoli, Gabriele Sileoni, Nicola Silvestri, Lorenzo Gabriele Tramacere, Lorenzo Cotrozzi   +15 more
doaj   +1 more source

Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral Measurements

Remote Sensing, 2014
Spectral Vegetation Indices (SVIs) have been widely used to indirectly detect plant diseases. The aim of this research is to evaluate the effect of different disease symptoms on SVIs and introduce suitable SVIs to detect rust disease.
Davoud Ashourloo, Mohammad Reza Mobasheri, Alfredo Huete   +2 more
doaj   +1 more source

Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity

International Journal of Environmental Research and Public Health, 2018
Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are ...
S. Keller, P. Maier, Felix M. Riese, S. Norra, A. Holbach, Nicolas Börsig, Andre Wilhelms, C. Moldaenke, A. Zaake, S. Hinz   +9 more
semanticscholar   +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

Nonlinear unmixing of minerals based on the log and continuum removal model

European Journal of Remote Sensing, 2019
Spectral mixing models for minerals can be complex, and choosing the right unmixing model is indispensable to ensure the accuracy of spectral unmixing. Continuum removal (CR) and natural log operation have the potential to eliminate nonlinear effects in ...
Hengqian Zhao, Xuesheng Zhao
doaj   +1 more source