Dimensionality reduction strategies for land use land cover classification based on airborne hyperspectral imagery: a survey
MA Moharram, DM Sundaram - Environmental Science and Pollution …, 2023 - Springer
Hyperspectral image (HSI) contains hundreds of adjacent spectral bands, which can
effectively differentiate the region of interest. Nevertheless, many irrelevant and highly …
effectively differentiate the region of interest. Nevertheless, many irrelevant and highly …
Segmentation-based linear discriminant analysis with information theoretic feature selection for hyperspectral image classification
The use of hyperspectral imaging sensors has greatly improved the classification of remotely
sensed data because of the abundant spectral information they offer. However, the …
sensed data because of the abundant spectral information they offer. However, the …
Effective hyperspectral image classification based on segmented PCA and 3D-2D CNN leveraging multibranch feature fusion
We present an innovative hyperspectral image (HSI) classification method addressing
challenges posed by closely spaced wavelength bands. Our approach combines 3D-2D …
challenges posed by closely spaced wavelength bands. Our approach combines 3D-2D …
DBANet: Dual-branch Attention Network for hyperspectral remote sensing image classification
Hyperspectral imaging technology produces images that capture both spatial and spectral
details of features, constituting a key data source in remote sensing detection. However, the …
details of features, constituting a key data source in remote sensing detection. However, the …
Advanced Plant Disease Segmentation in Precision Agriculture using Optimal Dimensionality Reduction with Fuzzy C-Means Clustering and Deep Learning
Analysis of hyperspectral imagery (HSI) is a critical aspect of remote sensing in precision
agriculture, for which effective dimensionality reduction (DR) strategies for the inherent …
agriculture, for which effective dimensionality reduction (DR) strategies for the inherent …
[PDF][PDF] HSIS-Net: Hyperspectral Image Segmentation Using Multi-view Active Learning Based FCSN.
Hyperspectral image (HSI) segmentation and classification is trending research in military
and civil applications area. However, HSI classification is facing various challenges in …
and civil applications area. However, HSI classification is facing various challenges in …
Subgrouping-based nmf with imbalanced class handling for hyperspectral image classification
The remote sensing industry is actively discussing the classification of hyperspectral images
(HSIs). For the first time, the idea of subgrouping dimensionality is presented using a …
(HSIs). For the first time, the idea of subgrouping dimensionality is presented using a …
Segmented Nonnegative Matrix Factorization for Hyperspectral Image Classification
The remote sensing hyperspectral image (HSI) consists of hundreds of narrow and adjoining
spectral bands. It carries a lot of significant information about the earth's objects. However …
spectral bands. It carries a lot of significant information about the earth's objects. However …
Spectrally Segmented Linear Discriminant Analysis for Hyperspectral Image Classification
MI Afjal, MNI Mondal… - 2022 25th International …, 2022 - ieeexplore.ieee.org
Remote sensing Hyperspectral Image (HSI) contains notable information about the earth's
objects which is actually obtained by hundreds of closely spaced spectral bands. Due to the …
objects which is actually obtained by hundreds of closely spaced spectral bands. Due to the …
Feature Extraction and Classification of Text Data by Combining Two-stage Feature Selection Algorithm and Improved Machine Learning Algorithm
H Huang - Informatica, 2024 - informatica.si
The generation of massive text data makes efficient text classification a key requirement for
information processing. However, the redundancy and uneven distribution of text data often …
information processing. However, the redundancy and uneven distribution of text data often …