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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 Novel Method for the Classification of Butterfly Species Using Pre-Trained CNN Models
Fathimathul Rajeena P. P., Rasha Orban, Kogilavani Shanmuga Vadivel, et al.
Electronics (2022) Vol. 11, Iss. 13, pp. 2016-2016
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

ML-DDoSnet: IoT Intrusion Detection Based on Denial-of-Service Attacks Using Machine Learning Methods and NSL-KDD
Mona Esmaeili, Seyedamiryousef Hosseini Goki, Behnam Hajipour Khire Masjidi, et al.
Wireless Communications and Mobile Computing (2022) Vol. 2022, pp. 1-16
Open Access | Times Cited: 41
Fusion of linear and non-linear dimensionality reduction techniques for feature reduction in LSTM-based Intrusion Detection System
Ankit Thakkar, Nandish Kikani, Rebakah Geddam
Applied Soft Computing (2024) Vol. 154, pp. 111378-111378
Closed Access | Times Cited: 13
Adaptive multi-view subspace learning based on distributed optimization
Wei Guo, Hangjun Che, Man-Fai Leung, et al.
Internet of Things (2024) Vol. 26, pp. 101203-101203
Closed Access | Times Cited: 7
Multi-objective SHADE with manta ray foraging optimizer for structural design problems
Changting Zhong, Gang Li, Zeng Meng, et al.
Applied Soft Computing (2023) Vol. 134, pp. 110016-110016
Open Access | Times Cited: 18
Quantum healthcare computing using precision based granular approach
Lakshita Aggarwal, Shelly Sachdeva, Puneet Goswami
Applied Soft Computing (2023) Vol. 144, pp. 110458-110458
Closed Access | Times Cited: 18
Mdebeia: Multi-Task Deep Learning for Butterfly Ecological Image Analysis
Kunkun Zhang, Xin Chen, Bin Wang
(2025)
Closed Access
Front-to-Side Hard and Soft Biometrics for Augmented Zero-Shot Side Face Recognition
Abdullah M. Al‐Subhi, Emad Sami Jaha
Sensors (2025) Vol. 25, Iss. 6, pp. 1638-1638
Open Access
Innovative deep learning solutions for Turkish butterfly species identification: a VGGNet enhancement study
Mustafa Teke, Gamze Elsamoly
Signal Image and Video Processing (2025) Vol. 19, Iss. 5
Closed Access
MdeBEIA: Multi-Task Deep Leaning for Butterfly Ecological Image Analysis
Kunkun Zhang, Xin Chen, Bin Wang
Digital Signal Processing (2025), pp. 105168-105168
Closed Access
Big Data Analytics Using Artificial Intelligence
Amir H. Gandomi, Fang Chen, Laith Abualigah
Electronics (2023) Vol. 12, Iss. 4, pp. 957-957
Open Access | Times Cited: 14
Categorization of Butterflies using Convolutional Neural Network
Kanwarpartap Singh Gill, Avinash Sharma, Vatsala Anand, et al.
(2023)
Closed Access | Times Cited: 13
Butterfly detection and classification techniques: A review
Rumana Yasmin, Aparna Das, Liton Jude Rozario, et al.
Intelligent Systems with Applications (2023) Vol. 18, pp. 200214-200214
Open Access | Times Cited: 12
Exploring the landscape of automated species identification apps: Development, promise, and user appraisal
Minh‐Xuan Truong, René van der Wal
BioScience (2024) Vol. 74, Iss. 9, pp. 601-613
Open Access | Times Cited: 4
Investigation of Applying Machine Learning and Hyperparameter Tuned Deep Learning Approaches for Arrhythmia Detection in ECG Images
S. V. Kogilavani, V E Sathishkumar, Sandeep Kumar Mathivanan, et al.
Computational and Mathematical Methods in Medicine (2022) Vol. 2022, pp. 1-12
Open Access | Times Cited: 18
New trends in detection of harmful insects and pests in modern agriculture using artificial neural networks. a review
Dan Popescu, Alexandru Dinca, Loretta Ichim, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 9
Enhanced harmony search for hyperparameter tuning of deep neural networks
Hindriyanto Dwi Purnomo, Tad Gonsalves, Teguh Wahyono, et al.
Soft Computing (2024) Vol. 28, Iss. 17-18, pp. 9905-9919
Closed Access | Times Cited: 2
Overview of Pest Detection and Recognition Algorithms
Boyu Guo, Jianji Wang, Minghui Guo, et al.
Electronics (2024) Vol. 13, Iss. 15, pp. 3008-3008
Open Access | Times Cited: 2
Automatic classification of parasitized fruit fly pupae from X-ray images by convolutional neural networks
Rangel Shida Marinho, Alysson Alexander Naves Silva, Clíssia Barboza da Silva, et al.
Ecological Informatics (2023) Vol. 78, pp. 102382-102382
Closed Access | Times Cited: 5
Butterflies Recognition using Enhanced Transfer Learning and Data Augmentation
Harish Trio Adityawan, Omar Farroq, Stefanus Santosa, et al.
Journal of Computing Theories and Applications (2023) Vol. 1, Iss. 2, pp. 115-128
Open Access | Times Cited: 4
A new efficient quorum planted (ℓ, d) motif search on ChIP-seq dataset using segmentation to filtration and freezing firefly algorithms
P. Theepalakshmi, U. Srinivasulu Reddy
Soft Computing (2023) Vol. 28, Iss. 4, pp. 3049-3070
Open Access | Times Cited: 2
A Classification method for Insects using Data Augmentation and Deep Neural Networks
Bui Hai Phong
International Journal of Advanced Research in Computer Science (2024) Vol. 15, Iss. 2, pp. 21-24
Open Access
Using CNN for Brain Tumor Diagnosis
Shravani Kulkarni, Piyush Bhosale, Susanta Das
Advances in medical diagnosis, treatment, and care (AMDTC) book series (2024), pp. 104-124
Closed Access
A chest imaging diagnosis report generation method based on dual-channel transmodal memory network
Zilong Dong, Jing Lian, Xiangzi Zhang, et al.
Biomedical Signal Processing and Control (2024) Vol. 100, pp. 107021-107021
Closed Access
AInsectID Version 1.1: an Insect Species Identification Software Based on the Transfer Learning of Deep Convolutional Neural Networks
Haleema Sadia, Parvez Alam
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Artificial intelligence correctly classifies developmental stages of monarch caterpillars enabling better conservation through the use of community science photographs
Naresh Neupane, Rhea Goswami, Kyle Robert Harrison, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
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