Mohammad Nur Nobi

545 total citations · 1 hit paper
3 papers, 219 citations indexed

About

Mohammad Nur Nobi is a scholar working on Artificial Intelligence, Computer Networks and Communications and Sociology and Political Science. According to data from OpenAlex, Mohammad Nur Nobi has authored 3 papers receiving a total of 219 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 1 paper in Computer Networks and Communications and 1 paper in Sociology and Political Science. Recurrent topics in Mohammad Nur Nobi's work include Anomaly Detection Techniques and Applications (2 papers), Generative Adversarial Networks and Image Synthesis (1 paper) and Privacy-Preserving Technologies in Data (1 paper). Mohammad Nur Nobi is often cited by papers focused on Anomaly Detection Techniques and Applications (2 papers), Generative Adversarial Networks and Image Synthesis (1 paper) and Privacy-Preserving Technologies in Data (1 paper). Mohammad Nur Nobi collaborates with scholars based in United States. Mohammad Nur Nobi's co-authors include Md. Shohel Rana, Andrew H. Sung, Beddhu Murali, James Benson, Smriti Bhatt and Ram Krishnan and has published in prestigious journals such as IEEE Access.

In The Last Decade

Mohammad Nur Nobi

3 papers receiving 197 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deepfake Detection: A Systematic Literature Review

2022 216 citations Md. Shohel Rana, Mohammad Nur Nobi et al. IEEE Access profile →

Peers

Countries citing papers authored by Mohammad Nur Nobi

Since Specialization

Citations

This map shows the geographic impact of Mohammad Nur Nobi'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 Mohammad Nur Nobi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Nur Nobi more than expected).

Fields of papers citing papers by Mohammad Nur Nobi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Nur Nobi. 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 Mohammad Nur Nobi. The network helps show where Mohammad Nur Nobi may publish in the future.

Co-authorship network of co-authors of Mohammad Nur Nobi

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Nur Nobi. A scholar is included among the top collaborators of Mohammad Nur Nobi 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 Mohammad Nur Nobi. Mohammad Nur Nobi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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3 of 3 papers shown

#	Work	Indexed citations
1	Environment Aware Deep Learning Based Access Control Model 2024 ·(unknown), Smriti Bhatt, (unknown), Mohammad Nur Nobi, James Benson, Ram Krishnan	1
2	DeepDistAL: Deepfake Dataset Distillation using Active Learning 2024 ·Md. Shohel Rana, Mohammad Nur Nobi, Andrew H. Sung	2
3	Deepfake Detection: A Systematic Literature Review breakdown → 2022 ·IEEE Access ·Md. Shohel Rana, Mohammad Nur Nobi, Beddhu Murali, Andrew H. Sung	216

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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