[HTML][HTML] Deep learning classifiers for hyperspectral imaging: A review
Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
Survey and insights into unmanned aerial-vehicle-based detection and documentation of clandestine graves and human remains
abstract Numerous biological and archaeological studies have demonstrated the legitimacy
of remote sensing in anthropology. This article focuses on detecting and documenting …
of remote sensing in anthropology. This article focuses on detecting and documenting …
Robust classification technique for hyperspectral images based on 3D-discrete wavelet transform
Hyperspectral image classification is an emerging and interesting research area that has
attracted several researchers to contribute to this field. Hyperspectral images have multiple …
attracted several researchers to contribute to this field. Hyperspectral images have multiple …
Automated georectification and mosaicking of UAV-based hyperspectral imagery from push-broom sensors
Hyperspectral systems integrated on unmanned aerial vehicles (UAV) provide unique
opportunities to conduct high-resolution multitemporal spectral analysis for diverse …
opportunities to conduct high-resolution multitemporal spectral analysis for diverse …
A low complexity hyperspectral image compression through 3D set partitioned embedded zero block coding
Memory management of the hyperspectral image sensor is a challenging issue. The existing
hyperspectral image compression schemes play a dominant role in minimizing the cost of …
hyperspectral image compression schemes play a dominant role in minimizing the cost of …
Reconstruction of Compressed Hyperspectral Image Using SqueezeNet Coupled Dense Attentional Net
D Mohan, J Aravinth, S Rajendran - Remote Sensing, 2023 - mdpi.com
This study addresses image denoising alongside the compression and reconstruction of
hyperspectral images (HSIs) using deep learning techniques, since the research community …
hyperspectral images (HSIs) using deep learning techniques, since the research community …
Low complexity block tree coding for hyperspectral image sensors
S Bajpai - Multimedia Tools and Applications, 2022 - Springer
Complexity of any onboard hyperspectral image sensor is a challenging issue. The existing
hyperspectral image compression algorithm plays a great role in reducing the data …
hyperspectral image compression algorithm plays a great role in reducing the data …
Analysis and prediction of land use/land cover changes and its impacts on the corridors of cattle grazing routes in Benue state, Nigeria
CA Odiji, HS Ahmad, MO Adepoju, B Odia… - Geology, Ecology …, 2024 - Taylor & Francis
It is becoming increasingly common for cattle grazing routes to be encroached upon and
changed to other land uses, and there is no clear indication of just how far these changes …
changed to other land uses, and there is no clear indication of just how far these changes …
[HTML][HTML] Extended morphological profiles analysis of airborne hyperspectral image classification using machine learning algorithms
When morphological capabilities are used for the class of high decision hyperspectral
photographs from metropolitan areas, one must not forget two crucial problems. Among …
photographs from metropolitan areas, one must not forget two crucial problems. Among …
S3AM: A Spectral-Similarity-Based Spatial Attention Module for Hyperspectral Image Classification
Recently, hyperspectral image (HSI) classification based on deep learning methods has
attracted growing attention and made great progress. Convolutional neural networks based …
attracted growing attention and made great progress. Convolutional neural networks based …