Results 21 to 30 of about 9,839 (245)
Methodology for determining deforestation areas in Lviv region using remote sensing data [PDF]
The object of the study is the processing of space images on the territory of the Carpathian territory in the Lviv region, obtained from the Landsat-8 satellite. The work aims to determine the area of deforestation in the Carpathian territory of the Lviv
Borys Chetverikov +3 more
doaj +1 more source
Unsupervised Band Selection for Hyperspectral Imagery Classification Without Manual Band Removal
The rich information available in hyperspectral imagery has provided significant opportunities for material classification and identification. Due to the problem of the “curse of dimensionality” (called Hughes phenomenon) posed by the high number of spectral channels along with small amounts of labeled training samples, dimensionality reduction is a ...
Sen Jia 0001 +3 more
openaire +1 more source
Unsupervised Band Selection of Hyperspectral Images via Multi-Dictionary Sparse Representation
Band selection is a direct and effective method to reduce the spectral dimension, which is one of popular topics in hyperspectral remote sensing. Recently, a number of methods were proposed to deal with the band selection problem.
Fei Li, Pingping Zhang, Lu Huchuan
doaj +1 more source
High Throughput Multispectral Image Processing with Applications in Food Science. [PDF]
Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image ...
Panagiotis Tsakanikas +2 more
doaj +1 more source
The high spectral resolution of hyperspectral images (HSIs) provides rich information but causes data redundancy, which imposes a computational burden on practical applications.
Zhou Zhang +5 more
doaj +1 more source
Unsupervised Band Selection in Hyperspectral Images using Autoencoder [PDF]
Hyperspectral images provide fine details of the observed scene from the exploitation of contiguous spectral bands. However, the high dimensionality of hyperspectral images causes a heavy burden on processing. Therefore, a common practice that has been largely adopted is the selection of bands before processing.
Habermann, Mateus +2 more
openaire +2 more sources
Spatial residual clustering and entropy based ranking for hyperspectral band selection
Though the Hyper-spectral images (HSI) are associated with rich spectral information for discriminating the class-specific objects, the high dimensional data generates Hughes effect for additional processing. So, during pre-processing, band Selection (BS)
Kishore Raju K. +2 more
doaj +1 more source
A comparative study of water indices and image classification algorithms for mapping inland water bodies using Landsat imagery was carried out through obtaining 24 high-resolution (≤5 m) and cloud-free images archived in Google Earth with the same (or ±1
Feifei Pan, Xiaohuan Xi, Cheng Wang
doaj +1 more source
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 +14 more
wiley +1 more source
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source

