Sheikh Nooruddin

1.4k total citations · 1 hit paper
17 papers, 866 citations indexed

About

Sheikh Nooruddin is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Computer Networks and Communications. According to data from OpenAlex, Sheikh Nooruddin has authored 17 papers receiving a total of 866 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 10 papers in Biomedical Engineering and 7 papers in Computer Networks and Communications. Recurrent topics in Sheikh Nooruddin's work include Context-Aware Activity Recognition Systems (9 papers), Non-Invasive Vital Sign Monitoring (9 papers) and IoT and Edge/Fog Computing (7 papers). Sheikh Nooruddin is often cited by papers focused on Context-Aware Activity Recognition Systems (9 papers), Non-Invasive Vital Sign Monitoring (9 papers) and IoT and Edge/Fog Computing (7 papers). Sheikh Nooruddin collaborates with scholars based in Bangladesh, Canada and United Arab Emirates. Sheikh Nooruddin's co-authors include Md. Milon Islam, Ghulam Muhammad, Fakhri Karray, Fakhri Karray, Md. Rabiul Islam, Muhammad Nomani Kabir, Md Asadul Islam, Muhammad Sheikh Sadi, Saifuddin Mahmud and L. J. Muhammad and has published in prestigious journals such as IEEE Access, IEEE Internet of Things Journal and Information Fusion.

In The Last Decade

Sheikh Nooruddin

17 papers receiving 825 citations

Hit Papers

Multi-level feature fusion for multimodal human activity ... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sheikh Nooruddin Bangladesh 13 395 265 221 197 148 17 866
Jian He China 13 296 0.7× 190 0.7× 243 1.1× 78 0.4× 137 0.9× 38 803
Girija Chetty Australia 18 500 1.3× 159 0.6× 218 1.0× 94 0.5× 77 0.5× 118 984
Monica Mordonini Italy 14 384 1.0× 252 1.0× 213 1.0× 146 0.7× 32 0.2× 52 1.0k
Tahmina Zebin United Kingdom 10 217 0.5× 116 0.4× 288 1.3× 216 1.1× 123 0.8× 19 631
Lourdes Martínez-Villaseñor Mexico 12 460 1.2× 305 1.2× 201 0.9× 93 0.5× 28 0.2× 45 695
Rodrigo Olivares Chile 14 133 0.3× 111 0.4× 210 1.0× 94 0.5× 44 0.3× 47 569
Hiren Kumar Thakkar India 14 158 0.4× 150 0.6× 116 0.5× 112 0.6× 36 0.2× 42 616
Sozo Inoue Japan 17 697 1.8× 255 1.0× 296 1.3× 284 1.4× 11 0.1× 117 1.1k
Saisakul Chernbumroong United Kingdom 10 380 1.0× 133 0.5× 102 0.5× 145 0.7× 21 0.1× 21 628
Badiea Abdulkarem Mohammed Saudi Arabia 19 197 0.5× 64 0.2× 364 1.6× 308 1.6× 128 0.9× 56 1.0k

Countries citing papers authored by Sheikh Nooruddin

Since Specialization
Citations

This map shows the geographic impact of Sheikh Nooruddin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sheikh Nooruddin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheikh Nooruddin more than expected).

Fields of papers citing papers by Sheikh Nooruddin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sheikh Nooruddin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sheikh Nooruddin. The network helps show where Sheikh Nooruddin may publish in the future.

Co-authorship network of co-authors of Sheikh Nooruddin

This figure shows the co-authorship network connecting the top 25 collaborators of Sheikh Nooruddin. A scholar is included among the top collaborators of Sheikh Nooruddin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sheikh Nooruddin. Sheikh Nooruddin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Islam, Md. Milon, Sheikh Nooruddin, Fakhri Karray, & Ghulam Muhammad. (2024). Enhanced multimodal emotion recognition in healthcare analytics: A deep learning based model-level fusion approach. Biomedical Signal Processing and Control. 94. 106241–106241. 18 indexed citations
2.
Islam, Md. Milon, Sheikh Nooruddin, Fakhri Karray, & Ghulam Muhammad. (2023). Multi-level feature fusion for multimodal human activity recognition in Internet of Healthcare Things. Information Fusion. 94. 17–31. 114 indexed citations breakdown →
3.
Nooruddin, Sheikh, Md. Milon Islam, Fakhri Karray, & Ghulam Muhammad. (2023). A multi-resolution fusion approach for human activity recognition from video data in tiny edge devices. Information Fusion. 100. 101953–101953. 16 indexed citations
4.
Islam, Md. Milon, Sheikh Nooruddin, Fakhri Karray, & Ghulam Muhammad. (2022). Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects. Computers in Biology and Medicine. 149. 106060–106060. 133 indexed citations
5.
Islam, Md. Milon, Sheikh Nooruddin, & Fakhri Karray. (2022). Multimodal Human Activity Recognition for Smart Healthcare Applications. 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 7 indexed citations
6.
Islam, Md. Milon, Sheikh Nooruddin, Fakhri Karray, & Ghulam Muhammad. (2022). Internet of Things Device Capabilities, Architectures, Protocols, and Smart Applications in Healthcare Domain: A Review. arXiv (Cornell University). 9 indexed citations
7.
Nooruddin, Sheikh, Md. Milon Islam, & Fakhri Karray. (2022). TinyHAR: Benchmarking Human Activity Recognition Systems in Resource Constrained Devices. 1–8. 4 indexed citations
8.
Islam, Md. Milon, Sheikh Nooruddin, Fakhri Karray, & Ghulam Muhammad. (2022). Internet of Things: Device Capabilities, Architectures, Protocols, and Smart Applications in Healthcare Domain. IEEE Internet of Things Journal. 10(4). 3611–3641. 67 indexed citations
9.
Rahman, Mohammad Marufur, et al.. (2021). HOG + CNN Net: Diagnosing COVID-19 and Pneumonia by Deep Neural Network from Chest X-Ray Images. SN Computer Science. 2(5). 371–371. 22 indexed citations
10.
Islam, Md. Milon, et al.. (2021). Scalable Telehealth Services to Combat Novel Coronavirus (COVID-19) Pandemic. SN Computer Science. 2(1). 18–18. 38 indexed citations
11.
Nooruddin, Sheikh, et al.. (2021). Sensor-based fall detection systems: a review. Journal of Ambient Intelligence and Humanized Computing. 13(5). 2735–2751. 66 indexed citations
12.
Islam, Md. Milon, Saifuddin Mahmud, L. J. Muhammad, et al.. (2020). Wearable Technology to Assist the Patients Infected with Novel Coronavirus (COVID-19). SN Computer Science. 1(6). 320–320. 86 indexed citations
13.
Nooruddin, Sheikh, et al.. (2020). A Bangladeshi License Plate Detection System Based on Extracted Color Features. 1–6. 5 indexed citations
14.
Islam, Md. Milon, et al.. (2020). Deep Learning Based Systems Developed for Fall Detection: A Review. IEEE Access. 8. 166117–166137. 88 indexed citations
15.
Nooruddin, Sheikh, et al.. (2019). An IoT based device-type invariant fall detection system. Internet of Things. 9. 100130–100130. 55 indexed citations
16.
Islam, Md Asadul, et al.. (2019). Developing IoT Based Smart Health Monitoring Systems: A Review. Revue d intelligence artificielle. 33(6). 435–440. 115 indexed citations
17.
Islam, Md. Manirul, et al.. (2019). A Review on Fall Detection Systems Using Data from Smartphone Sensors. Ingénierie des systèmes d information. 24(6). 569–576. 23 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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