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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:

Detection of early blight and late blight diseases on tomato leaves using hyperspectral imaging
Chuanqi Xie, Yongni Shao, Xiaoli Li, et al.
Scientific Reports (2015) Vol. 5, Iss. 1
Open Access | Times Cited: 154

Showing 1-25 of 154 citing articles:

Deep Learning for Tomato Diseases: Classification and Symptoms Visualization
Mohammed Brahimi, Kamel Boukhalfa, Abdelouahab Moussaoui
Applied Artificial Intelligence (2017) Vol. 31, Iss. 4, pp. 299-315
Closed Access | Times Cited: 714
Plant Disease Detection and Classification by Deep Learning—A Review
Lili Li, Shujuan Zhang, Bin Wang
IEEE Access (2021) Vol. 9, pp. 56683-56698
Open Access | Times Cited: 574
Close range hyperspectral imaging of plants: A review
Puneet Mishra, Mohd Shahrimie Mohd Asaari, Ana Herrero‐Langreo, et al.
Biosystems Engineering (2017) Vol. 164, pp. 49-67
Open Access | Times Cited: 260
Extraction of Spectral Information from Hyperspectral Data and Application of Hyperspectral Imaging for Food and Agricultural Products
Lankapalli Ravikanth, Digvir S. Jayas, N. D. G. White, et al.
Food and Bioprocess Technology (2016) Vol. 10, Iss. 1, pp. 1-33
Closed Access | Times Cited: 238
Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research
Maryam Ouhami, Adel Hafiane, Youssef Es-Saady, et al.
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2486-2486
Open Access | Times Cited: 177
Hyperspectral Imaging for Presymptomatic Detection of Tobacco Disease with Successive Projections Algorithm and Machine-learning Classifiers
Hongyan Zhu, Bingquan Chu, Chu Zhang, et al.
Scientific Reports (2017) Vol. 7, Iss. 1
Open Access | Times Cited: 172
Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection
Iftikhar Ahmad, Muhammad Hamid, Suhail Yousaf, et al.
Complexity (2020) Vol. 2020, pp. 1-6
Open Access | Times Cited: 149
Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review
Anton Terentev, В. И. Долженко, Alexander Fedotov, et al.
Sensors (2022) Vol. 22, Iss. 3, pp. 757-757
Open Access | Times Cited: 146
A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping
Taqdeer Gill, Simranveer Kaur Gill, Dinesh Kumar Saini, et al.
Phenomics (2022) Vol. 2, Iss. 3, pp. 156-183
Open Access | Times Cited: 141
On Using Artificial Intelligence and the Internet of Things for Crop Disease Detection: A Contemporary Survey
Houda Orchi, Mohamed Sadik, Mohammed Khaldoun
Agriculture (2021) Vol. 12, Iss. 1, pp. 9-9
Open Access | Times Cited: 107
Application of conventional UAV-based high-throughput object detection to the early diagnosis of pine wilt disease by deep learning
Bizhi Wu, Anjie Liang, Huafeng Zhang, et al.
Forest Ecology and Management (2021) Vol. 486, pp. 118986-118986
Closed Access | Times Cited: 106
Early identification of strawberry leaves disease utilizing hyperspectral imaging combing with spectral features, multiple vegetation indices and textural features
Gangshan Wu, Yinlong Fang, Qiyou Jiang, et al.
Computers and Electronics in Agriculture (2022) Vol. 204, pp. 107553-107553
Closed Access | Times Cited: 75
Hyperspectral Image Analysis and Machine Learning Techniques for Crop Disease Detection and Identification: A Review
Yimy Edisson García Vera, Mauricio Andrés Polochè Arango, Camilo A. Mendivelso-Fajardo, et al.
Sustainability (2024) Vol. 16, Iss. 14, pp. 6064-6064
Open Access | Times Cited: 20
New methods for improving the remote sensing estimation of soil organic matter content (SOMC) in the Ebinur Lake Wetland National Nature Reserve (ELWNNR) in northwest China
Xiaoping Wang, Zhang Fei, Hsiang‐te Kung, et al.
Remote Sensing of Environment (2018) Vol. 218, pp. 104-118
Closed Access | Times Cited: 151
Hyperspectral imaging for classification of healthy and gray mold diseased tomato leaves with different infection severities
Chuanqi Xie, Ce Yang, Yong He
Computers and Electronics in Agriculture (2017) Vol. 135, pp. 154-162
Closed Access | Times Cited: 128
Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato
Kaitlin M. Gold, Philip A. Townsend, Adam Chlus, et al.
Remote Sensing (2020) Vol. 12, Iss. 2, pp. 286-286
Open Access | Times Cited: 127
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Muhammad Adeel Asghar, Muhammad Jamil Khan, Fawad Fawad, et al.
Sensors (2019) Vol. 19, Iss. 23, pp. 5218-5218
Open Access | Times Cited: 93
Detection of Fusarium Head Blight in Wheat Using a Deep Neural Network and Color Imaging
Ruicheng Qiu, Ce Yang, Ali Moghimi, et al.
Remote Sensing (2019) Vol. 11, Iss. 22, pp. 2658-2658
Open Access | Times Cited: 83
Artificial intelligence in tomato leaf disease detection: a comprehensive review and discussion
Rajasekaran Thangaraj, S. Anandamurugan, P. Pandiyan, et al.
Journal of Plant Diseases and Protection (2021) Vol. 129, Iss. 3, pp. 469-488
Closed Access | Times Cited: 80
Close Range Spectral Imaging for Disease Detection in Plants Using Autonomous Platforms: a Review on Recent Studies
Puneet Mishra, G. Polder, Nastassia Vilfan
Current Robotics Reports (2020) Vol. 1, Iss. 2, pp. 43-48
Open Access | Times Cited: 72
High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement
Sumit Jangra, Vrantika Chaudhary, Ram C. Yadav, et al.
Phenomics (2021) Vol. 1, Iss. 2, pp. 31-53
Open Access | Times Cited: 70
Early Detection of Powdery Mildew Disease and Accurate Quantification of Its Severity Using Hyperspectral Images in Wheat
İmran Khan, Haiyan Liu, Wei Li, et al.
Remote Sensing (2021) Vol. 13, Iss. 18, pp. 3612-3612
Open Access | Times Cited: 63
Review: Holistic pest management against early blight disease towards sustainable agriculture
Keiji Jindo, A. Evenhuis, C. Kempenaar, et al.
Pest Management Science (2021) Vol. 77, Iss. 9, pp. 3871-3880
Open Access | Times Cited: 61
Wheat rust disease detection techniques: a technical perspective
Uferah Shafi, Rafia Mumtaz, Zunaira Shafaq, et al.
Journal of Plant Diseases and Protection (2022) Vol. 129, Iss. 3, pp. 489-504
Closed Access | Times Cited: 40
Intelligent agriculture: deep learning in UAV-based remote sensing imagery for crop diseases and pests detection
Hongyan Zhu, Chengzhi Lin, G. Liu, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 9
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