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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:

A review of deep learning used in the hyperspectral image analysis for agriculture
Chunying Wang, Baohua Liu, Lipeng Liu, et al.
Artificial Intelligence Review (2021) Vol. 54, Iss. 7, pp. 5205-5253
Closed Access | Times Cited: 198

Showing 1-25 of 198 citing articles:

A review of convolutional neural network architectures and their optimizations
Shuang Cong, Yang Zhou
Artificial Intelligence Review (2022) Vol. 56, Iss. 3, pp. 1905-1969
Closed Access | Times Cited: 141
Deep learning for near-infrared spectral data modelling: Hypes and benefits
Puneet Mishra, Dário Passos, Federico Marini, et al.
TrAC Trends in Analytical Chemistry (2022) Vol. 157, pp. 116804-116804
Open Access | Times Cited: 98
A review on the combination of deep learning techniques with proximal hyperspectral images in agriculture
Jayme Garcia Arnal Barbedo
Computers and Electronics in Agriculture (2023) Vol. 210, pp. 107920-107920
Closed Access | Times Cited: 62
A Survey on Deep Learning and Its Impact on Agriculture: Challenges and Opportunities
Marwan Ali Albahar
Agriculture (2023) Vol. 13, Iss. 3, pp. 540-540
Open Access | Times Cited: 43
The q-rung fuzzy LOPCOW-VIKOR model to assess the role of unmanned aerial vehicles for precision agriculture realization in the Agri-Food 4.0 era
Fatih Ecer, İlkin Yaran Ögel, R. Krishankumar, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. 11, pp. 13373-13406
Open Access | Times Cited: 43
A Systematic Review of Individual Tree Crown Detection and Delineation with Convolutional Neural Networks (CNN)
Haotian Zhao, Justin Morgenroth, Grant D. Pearse, et al.
Current Forestry Reports (2023) Vol. 9, Iss. 3, pp. 149-170
Open Access | Times Cited: 41
Spectral super-resolution meets deep learning: Achievements and challenges
Jiang He, Qiangqiang Yuan, Jie Li, et al.
Information Fusion (2023) Vol. 97, pp. 101812-101812
Open Access | Times Cited: 41
A research review on deep learning combined with hyperspectral Imaging in multiscale agricultural sensing
Luyu Shuai, Zhiyong Li, Ziao Chen, et al.
Computers and Electronics in Agriculture (2024) Vol. 217, pp. 108577-108577
Closed Access | Times Cited: 34
A systematic review of hyperspectral imaging in precision agriculture: Analysis of its current state and future prospects
Billy G. Ram, Peter G. Oduor, C. Igathinathane, et al.
Computers and Electronics in Agriculture (2024) Vol. 222, pp. 109037-109037
Open Access | Times Cited: 32
A comprehensive review of deep learning-based hyperspectral image reconstruction for agri-food quality appraisal
Md. Toukir Ahmed, Ocean Monjur, Alin Khaliduzzaman, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open Access | Times Cited: 3
Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why
Salvador Castillo‐Gironés, Sandra Munera, Marcelino Martı́nez-Sober, et al.
Computers and Electronics in Agriculture (2025) Vol. 230, pp. 109938-109938
Open Access | Times Cited: 1
Recent advances of deep learning algorithms for aquacultural machine vision systems with emphasis on fish
Daoliang Li, Ling Du
Artificial Intelligence Review (2021) Vol. 55, Iss. 5, pp. 4077-4116
Closed Access | Times Cited: 87
Hyperspectral Sensing of Plant Diseases: Principle and Methods
Long Wan, Hui Li, Chengsong Li, et al.
Agronomy (2022) Vol. 12, Iss. 6, pp. 1451-1451
Open Access | Times Cited: 57
Detection of Pesticide Residue Level in Grape Using Hyperspectral Imaging with Machine Learning
Weixin Ye, Tianying Yan, Chu Zhang, et al.
Foods (2022) Vol. 11, Iss. 11, pp. 1609-1609
Open Access | Times Cited: 56
Development of Deep Learning Methodology for Maize Seed Variety Recognition Based on Improved Swin Transformer
Chunguang Bi, Nan Hu, Yiqiang Zou, et al.
Agronomy (2022) Vol. 12, Iss. 8, pp. 1843-1843
Open Access | Times Cited: 43
Deep Learning in Medical Hyperspectral Images: A Review
Rong Cui, He Yu, Tingfa Xu, et al.
Sensors (2022) Vol. 22, Iss. 24, pp. 9790-9790
Open Access | Times Cited: 42
Integration of hyperspectral imaging and autoencoders: Benefits, applications, hyperparameter tunning and challenges
Garima Jaiswal, Ritu Rani, Harshita Mangotra, et al.
Computer Science Review (2023) Vol. 50, pp. 100584-100584
Closed Access | Times Cited: 38
Investigation into maize seed disease identification based on deep learning and multi-source spectral information fusion techniques
Peng Xu, Lixia Fu, Kang Xu, et al.
Journal of Food Composition and Analysis (2023) Vol. 119, pp. 105254-105254
Closed Access | Times Cited: 26
Applications of Hyperspectral Imaging Technology Combined with Machine Learning in Quality Control of Traditional Chinese Medicine from the Perspective of Artificial Intelligence: A Review
Yixia Pan, Hongxu Zhang, Yuan Chen, et al.
Critical Reviews in Analytical Chemistry (2023) Vol. 54, Iss. 8, pp. 2850-2864
Closed Access | Times Cited: 25
Prediction of fat content in salmon fillets based on hyperspectral imaging and residual attention convolution neural network
Wei Luo, Jing Zhang, Hai‐Hua Huang, et al.
LWT (2023) Vol. 184, pp. 115018-115018
Open Access | Times Cited: 25
Multiple vision architectures-based hybrid network for hyperspectral image classification
Feng Zhao, Junjie Zhang, Zhe Meng, et al.
Expert Systems with Applications (2023) Vol. 234, pp. 121032-121032
Closed Access | Times Cited: 23
DCTN: Dual-Branch Convolutional Transformer Network With Efficient Interactive Self-Attention for Hyperspectral Image Classification
Yunfei Zhou, Xiaohui Huang, Xiaofei Yang, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-16
Closed Access | Times Cited: 11
Early detection of Botrytis cinerea symptoms using deep learning multi-spectral image segmentation
Nikolaos Giakoumoglou, Eleni Kalogeropoulou, Christos Klaridopoulos, et al.
Smart Agricultural Technology (2024) Vol. 8, pp. 100481-100481
Open Access | Times Cited: 11
Progress in environmental monitoring and mitigation strategies for herbicides and insecticides: A comprehensive review
R. Kamalesh, S. Karishma, A. Saravanan
Chemosphere (2024) Vol. 352, pp. 141421-141421
Closed Access | Times Cited: 9
The application of hyperspectral imaging for wheat biotic and abiotic stress analysis: A review
Kun Zhang, Fangfang Yan, Ping Liu
Computers and Electronics in Agriculture (2024) Vol. 221, pp. 109008-109008
Closed Access | Times Cited: 9
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