A survey of human-in-the-loop for machine learning

X Wu, L Xiao, Y Sun, J Zhang, T Ma, L He - Future Generation Computer …, 2022 - Elsevier
Abstract Machine learning has become the state-of-the-art technique for many tasks
including computer vision, natural language processing, speech processing tasks, etc …

[HTML][HTML] A review on deep learning in UAV remote sensing

LP Osco, JM Junior, APM Ramos… - International Journal of …, 2021 - Elsevier
Abstract Deep Neural Networks (DNNs) learn representation from data with an impressive
capability, and brought important breakthroughs for processing images, time-series, natural …

Rotation-invariant attention network for hyperspectral image classification

X Zheng, H Sun, X Lu, W Xie - IEEE Transactions on Image …, 2022 - ieeexplore.ieee.org
Hyperspectral image (HSI) classification refers to identifying land-cover categories of pixels
based on spectral signatures and spatial information of HSIs. In recent deep learning-based …

Evolutionary deep learning: A survey

ZH Zhan, JY Li, J Zhang - Neurocomputing, 2022 - Elsevier
As an advanced artificial intelligence technique for solving learning problems, deep learning
(DL) has achieved great success in many real-world applications and attracted increasing …

Hyperspectral image classification—Traditional to deep models: A survey for future prospects

M Ahmad, S Shabbir, SK Roy, D Hong… - IEEE journal of …, 2021 - ieeexplore.ieee.org
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 …

Few-shot learning with class-covariance metric for hyperspectral image classification

B Xi, J Li, Y Li, R Song, D Hong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, embedding and metric-based few-shot learning (FSL) has been introduced into
hyperspectral image classification (HSIC) and achieved impressive progress. To further …

Category-specific prototype self-refinement contrastive learning for few-shot hyperspectral image classification

Q Liu, J Peng, N Chen, W Sun… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep learning (DL) has been extensively used for hyperspectral image classification (HSIC)
with significant success, but the classification of high-dimensional hyperspectral image (HSI) …

A semisupervised Siamese network for hyperspectral image classification

S Jia, S Jiang, Z Lin, M Xu, W Sun… - … on Geoscience and …, 2021 - ieeexplore.ieee.org
With the development of hyperspectral imaging technology, hyperspectral images (HSIs)
have become important when analyzing the class of ground objects. In recent years …

Integration of hyperspectral imaging and autoencoders: Benefits, applications, hyperparameter tunning and challenges

G Jaiswal, R Rani, H Mangotra, A Sharma - Computer Science Review, 2023 - Elsevier
Hyperspectral imaging (HSI) is a powerful tool that can capture and analyze a range of
spectral bands, providing unparalleled levels of precision and accuracy in data analysis …

Pneumonia classification from X-ray images with inception-V3 and convolutional neural network

M Mujahid, F Rustam, R Álvarez, J Luis Vidal Mazón… - Diagnostics, 2022 - mdpi.com
Pneumonia is one of the leading causes of death in both infants and elderly people, with
approximately 4 million deaths each year. It may be a virus, bacterial, or fungal, depending …