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IEEE Access

JournalCitation impact & published research

IEEE Access is a journal indexed in ScholarIQ from OpenAlex. ScholarIQ records 110,863 works, 2,529,655 citations, an h-index of 370 and an APC (USD) of 1,850.

110,863
Works
2,529,655
Citations
370
h-index
1,850
APC (USD)

What are the most-cited papers on IEEE Access?

ScholarIQmost cited works
Can AI Help in Screening Viral and COVID-19 Pneumonia?
Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar, Muhammad Abdul Kadir, Zaid Bin Mahbub, Khandaker Reajul Islam, Muhammad Salman Khan, Atif Iqbal, Nasser Al Emadi, Mamun Bin Ibne Reaz, Mohammad Tariqul Islam
IEEE Access. 20201,922 CitationsOPEN ACCESS
Machine Learning Applications for Precision Agriculture: A Comprehensive Review
Abhinav Sharma, Arpit Jain, Prateek Gupta, Vinay Chowdary
IEEE Access. 20201,053 CitationsOPEN ACCESS
Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook
Ricardo Silva Peres, Xiaodong Jia, Jay Lee, Keyi Sun, Armando Walter Colombo, José Barata
IEEE Access. 2020666 CitationsOPEN ACCESS
Heart Disease Identification Method Using Machine Learning Classification in E-Healthcare
Jianping Li, Amin Ul Haq, Salah Ud Din, Jalaluddin Khan, Asif Khan, Abdus Saboor
IEEE Access. 2020645 CitationsOPEN ACCESS
Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization
Tawsifur Rahman, Amith Khandakar, Muhammad Abdul Kadir, Khandaker Reajul Islam, Khandakar F. Islam, Rashid Mazhar, Tahir Hamid, Mohammad Tariqul Islam, Saad Bin Abul Kashem, Zaid Bin Mahbub, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury
IEEE Access. 2020636 CitationsOPEN ACCESS

Related on ScholarIQ

Can AI Help in Screening Viral and COVID-19 Pneumonia?
Paper
Machine Learning Applications for Precision Agriculture: A Comprehensive Review
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Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook
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Heart Disease Identification Method Using Machine Learning Classification in E-Healthcare
Paper
Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization
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Performance Analysis of Google Colaboratory as a Tool for Accelerating Deep Learning Applications
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470M+ articles · free account