Results 31 to 40 of about 9,721 (245)

Discovering the Representative Subset with Low Redundancy for Hyperspectral Feature Selection

Remote Sensing, 2019
In this paper, a novel unsupervised band selection (BS) criterion based on maximizing representativeness and minimizing redundancy (MRMR) is proposed for selecting a set of informative bands to represent the whole hyperspectral image cube.
Wenqiang Zhang, Xiaorun Li, Liaoying Zhao   +2 more
doaj   +1 more source

Transcriptional profiling of circulating extracellular vesicles from prebiopsy prostate cancer patients

Molecular Oncology, EarlyView.
RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner, Pierre Tennstedt, Randi C. Pose, Christian Müller, Katharina Besler, Svenja Schneegans, Malik Alawi, Marie C. Roesch, Sven Peine, Desiree Bonci, Joanna Budna‐Tukan, Evi Lianidou, Catherine Alix‐Panabières, Derya Tilki, Klaus Pantel   +14 more
wiley   +1 more source

A Method for Detection of Corn Kernel Mildew Based on Co-Clustering Algorithm with Hyperspectral Image Technology

Sensors, 2022
Hyperspectral imaging can simultaneously acquire spectral and spatial information of the samples and is, therefore, widely applied in the non-destructive detection of grain quality.
Zhen Kang, Tianchen Huang, Shan Zeng, Hao Li, Lei Dong, Chaofan Zhang   +5 more
doaj   +1 more source

Multiple-Feature Kernel-Based Probabilistic Clustering for Unsupervised Band Selection [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2019
This paper presents a new method to perform unsupervised band selection (UBS) with hyperspectral data. The method provides a probabilistic clustering approach. The band images are clustered in the image space by computing their posterior class probability.
Marco Bevilacqua, Yannick Berthoumieu
openaire   +1 more source

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Restoration and Calibration of Tilting Hyperspectral Super-Resolution Image

Sensors, 2020
Tilting sampling is a novel sampling mode for achieving a higher resolution of hyperspectral imagery. However, most studies on the tilting image have only focused on a single band, which loses the features of hyperspectral imagery.
Xizhen Zhang, Aiwu Zhang, Mengnan Li, Lulu Liu, Xiaoyan Kang   +4 more
doaj   +1 more source

Soil Moisture, Organic Carbon, and Nitrogen Content Prediction with Hyperspectral Data Using Regression Models

Sensors, 2022
Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production.
Dristi Datta, Manoranjan Paul, Manzur Murshed, Shyh Wei Teng, Leigh Schmidtke   +4 more
doaj   +1 more source

Understanding Further the Phenotypic Spectrum of Central Nervous System Inflammatory Demyelinating Disorders Using Unsupervised Clustering

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec, Elif Everest, Melih Tutuncu, Ugur Bilge, Sabahattin Saip, Ugur Uygunoglu, Aksel Siva   +6 more
wiley   +1 more source

Maximum simplex volume: an efficient unsupervised band selection method for hyperspectral image

IET Computer Vision, 2019
Hyperspectral imaging makes it possible to obtain object information with fine spectral resolution as well as spatial resolution, which is beneficial to a wide array of applications. However, there is a high correlation among the bands in a hyperspectral
Xuefeng Jiang, Lin Zhang, Junrui Liu, Shuying Li   +3 more
doaj   +1 more source

Mutual Information-Driven Feature Reduction for Hyperspectral Image Classification

Sensors, 2023
A hyperspectral image (HSI), which contains a number of contiguous and narrow spectral wavelength bands, is a valuable source of data for ground cover examinations.
Md Rashedul Islam, Boshir Ahmed, Md Ali Hossain, Md Palash Uddin   +3 more
doaj   +1 more source