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Publikováno v:
IEEE Access, Vol 12, Pp 93677-93688 (2024)
Hyperspectral image (HSI) classification has drawn increasing attention in the last decade. HSIs accurately classify terrestrial objects by capturing approximately contiguous spectral information. Owing to their excellent performance in image classif
Externí odkaz:
https://doaj.org/article/a6920eec53974d35bffa9bce5d90f0d8
Autor:
Bilal Ahmed, Tallha Akram, Syed Rameez Naqvi, Anas Alsuhaibani, Youssef N. Altherwy, Usman Masud
Publikováno v:
IEEE Access, Vol 12, Pp 91974-91998 (2024)
We propose a novel deep learning architecture, called XcelNet17, for image classification in remote sensing. Comprising fourteen convolutional and three fully connected layers, XcelNet17 outperforms several benchmark architectures available in the li
Externí odkaz:
https://doaj.org/article/f77118c58d994b04b2e0440545ff050f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11794-11808 (2024)
Semisupervised change detection (CD) methods have garnered increasing attention due to their capacity to alleviate the dependency of fully-supervised methods on a large number of pixel-level labels. These methods predominantly leverage generative adv
Externí odkaz:
https://doaj.org/article/51bed9a9409349a49ba596878be682d6
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11723-11740 (2024)
Convolutional neural network (CNN) has made significant progress in image superresolution (SR), which could thrash the limits of image spatial resolution. Recently, abundant CNN-based methods have been proposed for the remote sensing image SR; howeve
Externí odkaz:
https://doaj.org/article/ca184c51e6ae4f63ac6257cd31eefffd
Autor:
Nisar Ali, Ahmed Mohammed, Abdul Bais, Samia Berraies, Yuefeng Ruan, Richard D. Cuthbert, Jatinder S. Sangha
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11419-11433 (2024)
This study explored how to use UAV-based multispectral imaging, a plot detection model, and machine learning (ML) algorithms to predict wheat grain yield at the field scale. Multispectral data were collected over several weeks using the MicaSense Red
Externí odkaz:
https://doaj.org/article/a6934d62974c4d01bbc9cf68694a0cae
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11402-11418 (2024)
Building change detection (BCD) aims to identify new or disappeared buildings from bitemporal images. However, the varied scales and appearances of buildings, along with the challenge of pseudochange interference from complex backgrounds, make it dif
Externí odkaz:
https://doaj.org/article/28465589cd5e448da0b4c598c92ef975
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2655-2669 (2024)
Hyperspectral image (HSI) classification has become a popular research topic in recent years, and transformer-based networks have demonstrated superior performance by analyzing global semantic features. However, using transformers for pixel-level HSI
Externí odkaz:
https://doaj.org/article/5172e4668d1a44008cfc82952db647d0
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2705-2717 (2024)
Pansharpening is a fundamental and crucial image processing task for many remote sensing applications, which generates a high-resolution multispectral image by fusing a low-resolution multispectral image and a high-resolution panchromatic image. Rece
Externí odkaz:
https://doaj.org/article/4a4fe6af51c5446d9a2167dcb36a6b6e
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11050-11068 (2024)
In recent years, change detection (CD) methods have faced challenges in being applied to various types of remote sensing datasets and related research fields, particularly in the domain of CD in remote sensing images. While convolutional neural netwo
Externí odkaz:
https://doaj.org/article/ee8ac78aeadd45cd8fd5d23b8b0f4b1a
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10914-10928 (2024)
As urbanization accelerates, the evolving dynamics of village growth and decline have garnered widespread attention. Rural housing, as the most significant asset in villages, serves as the primary indicator of socioeconomic development in rural areas
Externí odkaz:
https://doaj.org/article/5f02eb0598c24c3288bd7cf85b240a78