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 …
Improving hyperspectral image classification through spectral-spatial feature reduction with a hybrid approach and deep learning
ABSTRACT The Hyperspectral Image (HSI) is a great source of information for observing the
earth's elements due to its numerous narrow and continuous spectral wavelength bands …
earth's elements due to its numerous narrow and continuous spectral wavelength bands …
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 …
Dimensionality reduction and classification for hyperspectral image based on robust supervised ISOMAP
S Ding, CA Keal, L Zhao, D Yu - Journal of Industrial and …, 2022 - Taylor & Francis
This study contributes to classification and recognition of hyperspectral image in industrial
sorting, mineral identification, geological exploration, environmental survey, and other …
sorting, mineral identification, geological exploration, environmental survey, and other …
Spectral segmentation based dimension reduction for hyperspectral image classification
Hyperspectral images (HSI) contain a wide range of information, the most prominent
technology for observing the earth. However, using an original HSI high-dimensional …
technology for observing the earth. However, using an original HSI high-dimensional …
Hyperspectral image classification via information theoretic dimension reduction
Hyperspectral images (HSIs) are one of the most successfully used tools for precisely and
potentially detecting key ground surfaces, vegetation, and minerals. HSIs contain a large …
potentially detecting key ground surfaces, vegetation, and minerals. HSIs contain a large …
Identification of duplicate parts of hyper spectral images based on fuzzy by dimensionality reduction techniques
S Pattem, S Thatavarti - Soft Computing, 2023 - Springer
Excessive data dimensionality can cause machine learning models to overfit, lowering the
accuracy of instance categorization. The most significant function in predictive analytics is …
accuracy of instance categorization. The most significant function in predictive analytics is …
Low-cost hyperspectral imaging to detect drought stress in high-throughput phenotyping
Recent developments in low-cost imaging hyperspectral cameras have opened up new
possibilities for high-throughput phenotyping (HTP), allowing for high-resolution spectral …
possibilities for high-throughput phenotyping (HTP), allowing for high-resolution spectral …
Hyperspectral images classification based on multiple kernel learning using SWT and KMNF with few training samples
S Hassanzadeh, H Danyali… - Journal of Spatial …, 2023 - Taylor & Francis
In this paper, a new techniquebased on Multiple kernel learning (MKL) with just a few
training samples is proposed for HSI classification utilising stationary wavelet transform …
training samples is proposed for HSI classification utilising stationary wavelet transform …