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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:

High performing ensemble of convolutional neural networks for insect pest image detection
Loris Nanni, Alessandro Manfè, Gianluca Maguolo, et al.
Ecological Informatics (2021) Vol. 67, pp. 101515-101515
Open Access | Times Cited: 78

Showing 1-25 of 78 citing articles:

A Systematic Review on Automatic Insect Detection Using Deep Learning
Ana Cláudia Teixeira, José Ribeiro, Raul Morais, et al.
Agriculture (2023) Vol. 13, Iss. 3, pp. 713-713
Open Access | Times Cited: 43
An Efficient Approach for Crops Pests Recognition and Classification Based on Novel DeepPestNet Deep Learning Model
Naeem Ullah, Javed Ali Khan, Lubna A. Alharbi, et al.
IEEE Access (2022) Vol. 10, pp. 73019-73032
Open Access | Times Cited: 62
Image Classification of Pests with Residual Neural Network Based on Transfer Learning
Chen Li, Zhen Tong, Zhihui Li
Applied Sciences (2022) Vol. 12, Iss. 9, pp. 4356-4356
Open Access | Times Cited: 46
Revolutionizing education: using computer simulation and cloud-based smart technology to facilitate successful open learning
Stamatios Papadakis, Арнольд Юхимович Ків, Hennadiy Kravtsov, et al.
(2023)
Open Access | Times Cited: 32
Exploring Deep Ensemble Model for Insect and Pest Detection from Images
Zeba Anwar, Sarfaraz Masood
Procedia Computer Science (2023) Vol. 218, pp. 2328-2337
Open Access | Times Cited: 25
Machine Learning for Precision Agriculture Using Imagery from Unmanned Aerial Vehicles (UAVs): A Survey
Imran Zualkernan, Diaa Addeen Abuhani, Maya Haj Hussain, et al.
Drones (2023) Vol. 7, Iss. 6, pp. 382-382
Open Access | Times Cited: 22
IoT Devices in Drones
Imdad Ali Shah, N. Z. Jhanjhi, Sayan Kumar Ray
Advances in information security, privacy, and ethics book series (2024), pp. 217-235
Closed Access | Times Cited: 13
Application of machine learning in automatic image identification of insects - a review
Yuanyi Gao, Xiaobao Xue, Guo‐Qing Qin, et al.
Ecological Informatics (2024) Vol. 80, pp. 102539-102539
Open Access | Times Cited: 10
CNN and transformer framework for insect pest classification
Yingshu Peng, Yi Wang
Ecological Informatics (2022) Vol. 72, pp. 101846-101846
Closed Access | Times Cited: 34
Genetic Algorithm-Based Hyperparameter Optimization for Convolutional Neural Networks in the Classification of Crop Pests
Enes Ayan
Arabian Journal for Science and Engineering (2023) Vol. 49, Iss. 3, pp. 3079-3093
Closed Access | Times Cited: 21
From identification to forecasting: the potential of image recognition and artificial intelligence for aphid pest monitoring
Philipp Batz, Torsten Will, Steffen Thiel, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 21
Varied Image Data Augmentation Methods for Building Ensemble
Riccardo Bravin, Loris Nanni, Andrea Loreggia, et al.
IEEE Access (2023) Vol. 11, pp. 8810-8823
Open Access | Times Cited: 17
Rice-YOLO: An Automated Insect Monitoring in Rice Storage Warehouses with the Deep Learning Model
P. Vinass Jamali, V. Eyarkai Nambi, M. Loganathan, et al.
ACS Agricultural Science & Technology (2025)
Closed Access
Self-supervised transformer-based pre-training method using latent semantic masking auto-encoder for pest and disease classification
Honglin Liu, Yongzhao Zhan, Huifen Xia, et al.
Computers and Electronics in Agriculture (2022) Vol. 203, pp. 107448-107448
Closed Access | Times Cited: 27
A method for detecting the quality of cotton seeds based on an improved ResNet50 model
Xinwu Du, Laiqiang Si, Pengfei Li, et al.
PLoS ONE (2023) Vol. 18, Iss. 2, pp. e0273057-e0273057
Open Access | Times Cited: 14
A two-stream network with complementary feature fusion for pest image classification
Chao Wang, Jinrui Zhang, Jin He, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106563-106563
Closed Access | Times Cited: 13
SDPH: a new technique for spatial detection of path holes from huge volume high-resolution raster images in near real-time
Murat Taşyürek
Journal of Real-Time Image Processing (2024) Vol. 21, Iss. 3
Open Access | Times Cited: 4
Efficient agricultural pest classification using vision transformer with hybrid pooled multihead attention
T. Saranya, C. Deisy, S. Sridevi
Computers in Biology and Medicine (2024) Vol. 177, pp. 108584-108584
Closed Access | Times Cited: 4
A New Hybrid ConvViT Model for Dangerous Farm Insect Detection
Anıl Utku, Mahmut Kaya, Yavuz Canbay
Applied Sciences (2025) Vol. 15, Iss. 5, pp. 2518-2518
Open Access
Applications of machine learning and deep learning in agriculture: A comprehensive review
Muhammad Waqas, Adila Naseem, Usa Wannasingha Humphries, et al.
Green Technologies and Sustainability (2025), pp. 100199-100199
Open Access
An ensemble learning integration of multiple CNN with improved vision transformer models for pest classification
Wanshang Xia, Dezhi Han, Dun Li, et al.
Annals of Applied Biology (2022) Vol. 182, Iss. 2, pp. 144-158
Closed Access | Times Cited: 19
ACNS Conference on Cloud and Immersive Technologies in Education: Report
Stamatios Papadakis, Arnold Kiv, Hennadiy Kravtsov, et al.
CTE Workshop Proceedings (2023) Vol. 10, pp. 1-44
Open Access | Times Cited: 12
Fruit fly automatic detection and monitoring techniques: A review
Florence Lello, Mussa Ally Dida, Mbazingwa E. Mkiramweni, et al.
Smart Agricultural Technology (2023) Vol. 5, pp. 100294-100294
Open Access | Times Cited: 12
Hybrid time series models with exogenous variable for improved yield forecasting of major Rabi crops in India
Pramit Pandit, Atish Sagar, Bikramjeet Ghose, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 12
Leaf Diseases Prediction Pest Detection and Pesticides Recommendation using Deep Learning Techniques
V Rajeshram, B Rithish, S. Karthikeyan, et al.
2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) (2023), pp. 1633-1639
Closed Access | Times Cited: 10
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