Tanvir Mahmud

1.1k total citations · 1 hit paper
32 papers, 774 citations indexed

About

Tanvir Mahmud is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Tanvir Mahmud has authored 32 papers receiving a total of 774 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 9 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Artificial Intelligence. Recurrent topics in Tanvir Mahmud's work include COVID-19 diagnosis using AI (9 papers), EEG and Brain-Computer Interfaces (7 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Tanvir Mahmud is often cited by papers focused on COVID-19 diagnosis using AI (9 papers), EEG and Brain-Computer Interfaces (7 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Tanvir Mahmud collaborates with scholars based in Bangladesh, United States and Canada. Tanvir Mahmud's co-authors include Shaikh Anowarul Fattah, Md Awsafur Rahman, Mohammad Saquib, Diana Marculescu, Sun‐Yuan Kung, M. Omair Ahmad, Wei‐Ping Zhu, Mohammad Ali, Shams Nafisa Ali and Yapeng Tian and has published in prestigious journals such as IEEE Access, IEEE Transactions on Industrial Informatics and IEEE Sensors Journal.

In The Last Decade

Tanvir Mahmud

30 papers receiving 744 citations

Hit Papers

align trajectories

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.

CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimization

2020 373 citations Tanvir Mahmud, Md Awsafur Rahman et al. Computers in Biology and Medicine profile →

Peers

Tanvir Mahmud

RNMI

AI

CVPR

PRM

HI

Ziquan Zhu United Kingdom

Murat Seçkin Ayhan Germany

Basil Mustafa Switzerland

Adeel Abbasi Pakistan

V. S. Chouhan India

Rayan Krishnan United States

Rongjun Ge China

Norliza Mohd Noor Malaysia

Deevyankar Agarwal Spain

Onur Osman Türkiye

Ziquan Zhu United Kingdom

Tanvir Mahmud

240 ×0.5

RNMI

217 ×0.6

AI

171 ×1.0

CVPR

41 ×0.5

PRM

26 ×0.3

HI

Citations per year, relative to Tanvir Mahmud Tanvir Mahmud (= 1×) peers Ziquan Zhu

Countries citing papers authored by Tanvir Mahmud

Since Specialization

Citations

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

Fields of papers citing papers by Tanvir Mahmud

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tanvir Mahmud. 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 Tanvir Mahmud. The network helps show where Tanvir Mahmud may publish in the future.

Co-authorship network of co-authors of Tanvir Mahmud

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Mahmud, Tanvir, et al.. (2025). Smart-LungNet for Lung Disease Classification. International Journal of Innovative Science and Research Technology (IJISRT). 233–233. 1 indexed citations

2.

Mahmud, Tanvir, Mustafa Munir, Radu Mărculescu, & Diana Marculescu. (2025). Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior. 940–949.

3.

Mahmud, Tanvir, Shentong Mo, Yapeng Tian, & Diana Marculescu. (2024). MA-AVT: Modality Alignment for Parameter-Efficient Audio-Visual Transformers. 7996–8005. 2 indexed citations

4.

Mahmud, Tanvir, et al.. (2024). Predicting polycystic ovary syndrome using SVM. International Journal of Science and Research Archive. 13(2). 4400–4408. 2 indexed citations

5.

Mahmud, Tanvir, Yapeng Tian, & Diana Marculescu. (2024). T-VSL: Text-Guided Visual Sound Source Localization in Mixtures. 26732–26741. 6 indexed citations

6.

Mahmud, Tanvir, Chun-Hao Liu, Burhaneddin Yaman, & Diana Marculescu. (2024). SSVOD: Semi-Supervised Video Object Detection with Sparse Annotations. 6759–6768. 5 indexed citations

7.

Rahman, Md Awsafur, et al.. (2023). CIFF-Net: Contextual image feature fusion for Melanoma diagnosis. Biomedical Signal Processing and Control. 88. 105673–105673. 12 indexed citations

8.

Mahmud, Tanvir, et al.. (2023). CLIP4VideoCap: Rethinking Clip for Video Captioning with Multiscale Temporal Fusion and Commonsense Knowledge. 1–5. 3 indexed citations

9.

Mahmud, Tanvir & Diana Marculescu. (2023). AVE-CLIP: AudioCLIP-based Multi-window Temporal Transformer for Audio Visual Event Localization. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 5147–5156. 20 indexed citations

10.

Mahmud, Tanvir, et al.. (2022). A dual-stage deep convolutional neural network for automatic diagnosis of COVID-19 and pneumonia from chest CT images. Computers in Biology and Medicine. 149. 105806–105806. 16 indexed citations

11.

Ali, Mohammad, et al.. (2021). AutoCovNet: Unsupervised feature learning using autoencoder and feature merging for detection of COVID-19 from chest X-ray images. Journal of Applied Biomedicine. 41(4). 1685–1701. 25 indexed citations

12.

Mahmud, Tanvir, et al.. (2021). Sleep Apnea Detection From Variational Mode Decomposed EEG Signal Using a Hybrid CNN-BiLSTM. IEEE Access. 9. 102355–102367. 30 indexed citations

13.

Mahmud, Tanvir, Md Awsafur Rahman, Shaikh Anowarul Fattah, & Sun‐Yuan Kung. (2021). CovSegNet: A Multi Encoder–Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans. IEEE Transactions on Artificial Intelligence. 2(3). 283–297. 24 indexed citations

14.

Mahmud, Tanvir, Md Awsafur Rahman, & Shaikh Anowarul Fattah. (2020). CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimization. Computers in Biology and Medicine. 122. 103869–103869. 373 indexed citations breakdown →

15.

Mahmud, Tanvir, et al.. (2020). CovTANet: A Hybrid Tri-Level Attention-Based Network for Lesion Segmentation, Diagnosis, and Severity Prediction of COVID-19 Chest CT Scans. IEEE Transactions on Industrial Informatics. 17(9). 6489–6498. 31 indexed citations

16.

Mahmud, Tanvir, et al.. (2020). PolypSegNet: A modified encoder-decoder architecture for automated polyp segmentation from colonoscopy images. Computers in Biology and Medicine. 128. 104119–104119. 73 indexed citations

17.

Ali, Mohammad, et al.. (2020). Transfer Learning Based Method for COVID-19 Detection From Chest X-ray Images. 585–590. 8 indexed citations

18.

Mahmud, Tanvir, et al.. (2020). A Novel Multi-Stage Training Approach for Human Activity Recognition From Multimodal Wearable Sensor Data Using Deep Neural Network. IEEE Sensors Journal. 21(2). 1715–1726. 32 indexed citations

19.

Mahmud, Tanvir, et al.. (2020). A Multi-Model Based Ensembling Approach to Detect COVID-19 from Chest X-Ray Images. 591–595. 5 indexed citations

20.

Mahmud, Tanvir, et al.. (2020). Human Activity Recognition From Multi-modal Wearable Sensor Data Using Deep Multi-stage LSTM Architecture Based on Temporal Feature Aggregation. 249–252. 16 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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