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Anupam Kumar Bairagi
ResearcherPublications, citations & collaboration network
Anupam Kumar Bairagi is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 102 works, 3,497 citations, an h-index of 29 and an i10-index of 47.
102
Works
3,497
Citations
29
h-index
47
i10-index
How has Anupam Kumar Bairagi's publication output changed over time?
ScholarIQpublication output · 2019–2025
Output grew0% over the shown period — from 1 works in 2019 to 1 in 2025.
1
4
2
2
1
1
201920212022202320242025
What are the most-cited papers on Anupam Kumar Bairagi?
ScholarIQmost cited works
A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework
Mehedi Masud, Niloy Sikder, Abdullah-Al Nahid, Anupam Kumar Bairagi, Mohammed A. AlZain
Sensors. 2021457 CitationsOPEN ACCESS
IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review
Suliman Abdulmalek, Abdul Nasir, Waheb A. Jabbar, Mukarram A. M. Almuhaya, Anupam Kumar Bairagi, Md. Al-Masrur Khan, Seong‐Hoon Kee
Healthcare. 2022426 CitationsOPEN ACCESS
Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach
Madyan Alsenwi, Nguyen H. Tran, Mehdi Bennis, Shashi Raj Pandey, Anupam Kumar Bairagi, Choong Seon Hong
S4306400284. 2021325 Citations
Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning
Nusrat Jahan Prottasha, Abdullah As Sami, Md. Kowsher, Saydul Akbar Murad, Anupam Kumar Bairagi, Mehedi Masud, Mohammed Baz
Sensors. 2022242 CitationsOPEN ACCESS
eMBB-URLLC Resource Slicing: A Risk-Sensitive Approach
Madyan Alsenwi, Nguyen H. Tran, Mehdi Bennis, Anupam Kumar Bairagi, Choong Seon Hong
S147316732. 2019228 CitationsOPEN ACCESS
Related on ScholarIQ
Khulna University
Institution
A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework
Paper
IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review
Paper
Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach
Paper
Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning
Paper
eMBB-URLLC Resource Slicing: A Risk-Sensitive Approach
Paper