Machine Learning and Knowledge Extraction | Top Cited Papers from the USA in 2022–2023

Machine Learning and Knowledge Extraction (ISSN: 2504-4990) is an international, peer-reviewed, open access journal on machine learning and applications. It publishes original research articles, reviews, tutorials, research ideas, short notes and Special Issues that focus on machine learning and applications.

We welcome you to read our most highly cited papers from the USA in 2022 and 2023, which are listed below:

1. “Machine Learning Based Restaurant Sales Forecasting”
by Austin Schmidt, Md Wasi Ul Kabir and Md Tamjidul Hoque
Mach. Learn. Knowl. Extr. 2022, 4(1), 105-130; https://doi.org/10.3390/make4010006
Available online: https://www.mdpi.com/2504-4990/4/1/6

2. “Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication”
by Nyle Siddiqui, Rushit Dave, Mounika Vanamala and Naeem Seliya
Mach. Learn. Knowl. Extr. 2022, 4(2), 502-518; https://doi.org/10.3390/make4020023
Available online: https://www.mdpi.com/2504-4990/4/2/23

3. “TabFairGAN: Fair Tabular Data Generation with Generative Adversarial Networks”
by Amirarsalan Rajabi and Ozlem Ozmen Garibay
Mach. Learn. Knowl. Extr. 2022, 4(2), 488-501; https://doi.org/10.3390/make4020022
Available online: https://www.mdpi.com/2504-4990/4/2/22

4. “Semantic Image Segmentation Using Scant Pixel Annotations”
by Adithi D. Chakravarthy, Dilanga Abeyrathna, Mahadevan Subramaniam, Parvathi Chundi and Venkataramana Gadhamshetty
Mach. Learn. Knowl. Extr. 2022, 4(3), 621-640; https://doi.org/10.3390/make4030029
Available online: https://www.mdpi.com/2504-4990/4/3/29

5. “A Morphological Post-Processing Approach for Overlapped Segmentation of Bacterial Cell Images”
by Dilanga Abeyrathna, Shailabh Rauniyar, Rajesh K. Sani and Pei-Chi Huang
Mach. Learn. Knowl. Extr. 2022, 4(4), 1024-1041; https://doi.org/10.3390/make4040052
Available online: https://www.mdpi.com/2504-4990/4/4/52

6. “Drug-Drug Interaction Extraction from Biomedical Text Using Relation BioBERT with BLSTM”
by Maryam KafiKang and Abdeltawab Hendawi
Mach. Learn. Knowl. Extr. 2023, 5(2), 669-683; https://doi.org/10.3390/make5020036
Available online: https://www.mdpi.com/2504-4990/5/2/36

7. “Improving Deep Learning for Maritime Remote Sensing through Data Augmentation and Latent Space”
by Daniel Sobien, Erik Higgins, Justin Krometis, Justin Kauffman and Laura Freeman
Mach. Learn. Knowl. Extr. 2022, 4(3), 665-687; https://doi.org/10.3390/make4030031
Available online: https://www.mdpi.com/2504-4990/4/3/31

8. “Developing a Novel Fair-Loan Classifier through a Multi-Sensitive Debiasing Pipeline: DualFair”
by Arashdeep Singh, Jashandeep Singh, Ariba Khan and Amar Gupta
Mach. Learn. Knowl. Extr. 2022, 4(1), 240-253; https://doi.org/10.3390/make4010011
Available online: https://www.mdpi.com/2504-4990/4/1/11

9. “Automatic Extraction of Medication Information from Cylindrically Distorted Pill Bottle Labels”
by Kseniia Gromova and Vinayak Elangovan
Mach. Learn. Knowl. Extr. 2022, 4(4), 852-864; https://doi.org/10.3390/make4040043
Available online: https://www.mdpi.com/2504-4990/4/4/43

10. “On Deceiving Malware Classification with Section Injection”
by Adeilson Antonio da Silva and Mauricio Pamplona Segundo
Mach. Learn. Knowl. Extr. 2023, 5(1), 144-168; https://doi.org/10.3390/make5010009
Available online: https://www.mdpi.com/2504-4990/5/1/9