Hyperspectral image classification—Traditional to deep models: A survey for future prospects
Hyperspectral imaging (HSI) has been extensively utilized in many real-life applications
because it benefits from the detailed spectral information contained in each pixel. Notably …
because it benefits from the detailed spectral information contained in each pixel. Notably …
Conventional to deep ensemble methods for hyperspectral image classification: A comprehensive survey
Hyperspectral image classification (HSIC) has become a hot research topic. Hyperspectral
imaging (HSI) has been widely used in a wide range of real-world application areas due to …
imaging (HSI) has been widely used in a wide range of real-world application areas due to …
A survey of intelligent transmission line inspection based on unmanned aerial vehicle
Y Luo, X Yu, D Yang, B Zhou - Artificial Intelligence Review, 2023 - Springer
With the development of the new generation of information technology, artificial intelligence,
cloud computing and big data are gradually becoming powerful engines of the smart grid. In …
cloud computing and big data are gradually becoming powerful engines of the smart grid. In …
Automatic fault diagnosis of infrared insulator images based on image instance segmentation and temperature analysis
B Wang, M Dong, M Ren, Z Wu, C Guo… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
As an onsite condition monitoring method, an infrared inspection can help to discover and
analyze abnormal temperature increases in power equipment. For improving the efficiency …
analyze abnormal temperature increases in power equipment. For improving the efficiency …
Deep learning based module defect analysis for large-scale photovoltaic farms
X Li, Q Yang, Z Lou, W Yan - IEEE Transactions on Energy …, 2018 - ieeexplore.ieee.org
The efficient condition monitoring and accurate module defect detection in large-scale
photovoltaic (PV) farms demand for novel inspection method and analysis tools. This paper …
photovoltaic (PV) farms demand for novel inspection method and analysis tools. This paper …
Multi-sensor image fusion: a survey of the state of the art
B Li, Y Xian, D Zhang, J Su… - Journal of …, 2021 - research.europeanlibrarypress.com
Image fusion has been developing into an important area of research. In remote sensing, the
use of the same image sensor in different working modes, or different image sensors, can …
use of the same image sensor in different working modes, or different image sensors, can …
Desert low-frequency noise suppression by using adaptive DnCNNs based on the determination of high-order statistic
XT Dong, Y Li, BJ Yang - Geophysical Journal International, 2019 - academic.oup.com
The importance of low-frequency seismic data has been already recognized by
geophysicists. However, there are still a number of obstacles that must be overcome for …
geophysicists. However, there are still a number of obstacles that must be overcome for …
Water-quality classification of inland lakes using Landsat8 images by convolutional neural networks
F Pu, C Ding, Z Chao, Y Yu, X Xu - Remote Sensing, 2019 - mdpi.com
Water-quality monitoring of inland lakes is essential for freshwater-resource protection. In
situ water-quality measurements and ratings are accurate but high costs limit their usage …
situ water-quality measurements and ratings are accurate but high costs limit their usage …
A spatial-channel progressive fusion ResNet for remote sensing classification
In recent years, the panchromatic (PAN) and the multispectral (MS) remote sensing images
classification has become a research hotspot. In this paper, we propose a spatial-channel …
classification has become a research hotspot. In this paper, we propose a spatial-channel …
Very high resolution remote sensing image classification with SEEDS-CNN and scale effect analysis for superpixel CNN classification
X Lv, D Ming, YY Chen, M Wang - International Journal of Remote …, 2019 - Taylor & Francis
Pixel-based convolutional neural network (CNN) has demonstrated good performance in the
classification of very high resolution images (VHRI) from which abstract deep features are …
classification of very high resolution images (VHRI) from which abstract deep features are …