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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Hyperspectral Band Selection Using Attention-Based Convolutional Neural Networks
Pablo Ribalta Lorenzo, Łukasz Tulczyjew, Michał Marcinkiewicz, et al.
IEEE Access (2020) Vol. 8, pp. 42384-42403
Open Access | Times Cited: 81

Showing 1-25 of 81 citing articles:

A Similarity-Based Ranking Method for Hyperspectral Band Selection
Buyun Xu, Xihai Li, Weijun Hou, et al.
IEEE Transactions on Geoscience and Remote Sensing (2021) Vol. 59, Iss. 11, pp. 9585-9599
Closed Access | Times Cited: 77
Deep Reinforcement Learning for Semisupervised Hyperspectral Band Selection
Jie Feng, Di Li, Jing Gu, et al.
IEEE Transactions on Geoscience and Remote Sensing (2021) Vol. 60, pp. 1-19
Closed Access | Times Cited: 69
Attention Mechanism and Depthwise Separable Convolution Aided 3DCNN for Hyperspectral Remote Sensing Image Classification
Wenmei Li, Huaihuai Chen, Qing Liu, et al.
Remote Sensing (2022) Vol. 14, Iss. 9, pp. 2215-2215
Open Access | Times Cited: 45
A deep convolutional neural network-based wavelength selection method for spectral characteristics of rice blast disease
Shuai Feng, Dongxue Zhao, Qiang Guan, et al.
Computers and Electronics in Agriculture (2022) Vol. 199, pp. 107199-107199
Closed Access | Times Cited: 40
Taking Artificial Intelligence Into Space Through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “brain” close to the “eyes” of satellite missions
Agata M. Wijata, M.F. Foulon, Yves Bobichon, et al.
IEEE Geoscience and Remote Sensing Magazine (2023) Vol. 11, Iss. 2, pp. 10-39
Closed Access | Times Cited: 26
RDTN: Residual Densely Transformer Network for hyperspectral image classification
Yan Li, Xiaofei Yang, Dong Tang, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123939-123939
Closed Access | Times Cited: 10
Onboard Processing of Hyperspectral Imagery: Deep Learning Advancements, Methodologies, Challenges, and Emerging Trends
Nafiseh Ghasemi, Jon Alvarez Justo, Marco Celesti, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2025) Vol. 18, pp. 4780-4790
Open Access | Times Cited: 1
Combining Multi-Dimensional Convolutional Neural Network (CNN) With Visualization Method for Detection of Aphis gossypii Glover Infection in Cotton Leaves Using Hyperspectral Imaging
Tianying Yan, Wei Xu, Lin Jiao, et al.
Frontiers in Plant Science (2021) Vol. 12
Open Access | Times Cited: 50
Marginalized Graph Self-Representation for Unsupervised Hyperspectral Band Selection
Yongshan Zhang, Xinxin Wang, Xinwei Jiang, et al.
IEEE Transactions on Geoscience and Remote Sensing (2021) Vol. 60, pp. 1-12
Closed Access | Times Cited: 49
Towards On-Board Hyperspectral Satellite Image Segmentation: Understanding Robustness of Deep Learning through Simulating Acquisition Conditions
Jakub Nalepa, Michał Myller, Marcin Cwiek, et al.
Remote Sensing (2021) Vol. 13, Iss. 8, pp. 1532-1532
Open Access | Times Cited: 44
An attention-driven convolutional neural network-based multi-level spectral–spatial feature learning for hyperspectral image classification
Chunyu Pu, Hong Huang, Liping Yang
Expert Systems with Applications (2021) Vol. 185, pp. 115663-115663
Closed Access | Times Cited: 42
A Hybrid Gray Wolf Optimizer for Hyperspectral Image Band Selection
Yulei Wang, Qingyu Zhu, Haipeng Ma, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-13
Closed Access | Times Cited: 35
Maize seed fraud detection based on hyperspectral imaging and one-class learning
Liu Zhang, Yaoguang Wei, Jincun Liu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108130-108130
Closed Access | Times Cited: 8
Dual-stream spectral-spatial convolutional neural network for hyperspectral image classification and optimal band selection
Şaziye Özge Atik
Advances in Space Research (2024) Vol. 74, Iss. 5, pp. 2025-2041
Closed Access | Times Cited: 8
Efficient Graph Convolutional Self-Representation for Band Selection of Hyperspectral Image
Yaoming Cai, Zijia Zhang, Xiaobo Liu, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2020) Vol. 13, pp. 4869-4880
Open Access | Times Cited: 49
A Review of Unsupervised Band Selection Techniques: Land Cover Classification for Hyperspectral Earth Observation Data
Ram Narayan Patro, Subhashree Subudhi, Pradyut Kumar Biswal, et al.
IEEE Geoscience and Remote Sensing Magazine (2021) Vol. 9, Iss. 3, pp. 72-111
Closed Access | Times Cited: 40
A Pixel Cluster CNN and Spectral-Spatial Fusion Algorithm for Hyperspectral Image Classification With Small-Size Training Samples
Shuxian Dong, Yinghui Quan, Wei Feng, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2021) Vol. 14, pp. 4101-4114
Open Access | Times Cited: 33
A Multiscale Superpixel-Level Group Clustering Framework for Hyperspectral Band Selection
Sen Jia, Yue Yuan, Nanying Li, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-18
Closed Access | Times Cited: 25
Improved learning by using a modified activation function of a Convolutional Neural Network in multi-spectral image classification
R. Vasanthakumari, Rakesh Vasudevan Nair, Venkatesh Gowda Krishnappa
Machine Learning with Applications (2023) Vol. 14, pp. 100502-100502
Open Access | Times Cited: 16
A Review of Deep Learning-Based Anomaly Detection Strategies in Industry 4.0 Focused on Application Fields, Sensing Equipment, and Algorithms
Adriano Liso, Angelo Cardellicchio, Cosimo Patruno, et al.
IEEE Access (2024) Vol. 12, pp. 93911-93923
Open Access | Times Cited: 6
Deep clustering using 3D attention convolutional autoencoder for hyperspectral image analysis
Ziyou Zheng, Shuzhen Zhang, Hailong Song, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Y–Net: Identification of Typical Diseases of Corn Leaves Using a 3D–2D Hybrid CNN Model Combined with a Hyperspectral Image Band Selection Module
Yinjiang Jia, Yaoyao Shi, Jiaqi Luo, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1494-1494
Open Access | Times Cited: 13
Ensemble synthetic oversampling with pixel pair for class-imbalanced and small-sized hyperspectral data classification
Wei Feng, Yijun Long, Gabriel Dauphin, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 128, pp. 103697-103697
Open Access | Times Cited: 4
Triple-Attention-Based Parallel Network for Hyperspectral Image Classification
Lei Qu, Xingliang Zhu, Jiannan Zheng, et al.
Remote Sensing (2021) Vol. 13, Iss. 2, pp. 324-324
Open Access | Times Cited: 27
Band selection strategies for hyperspectral image classification based on machine learning and artificial intelligent techniques –Survey
Shrutika S. Sawant, Prabukumar Manoharan, L. Agilandeeswari
Arabian Journal of Geosciences (2021) Vol. 14, Iss. 7
Closed Access | Times Cited: 26
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