Mohammad Zavid Parvez

1.5k total citations · 1 hit paper
46 papers, 982 citations indexed

About

Mohammad Zavid Parvez is a scholar working on Cognitive Neuroscience, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Mohammad Zavid Parvez has authored 46 papers receiving a total of 982 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Cognitive Neuroscience, 15 papers in Signal Processing and 11 papers in Artificial Intelligence. Recurrent topics in Mohammad Zavid Parvez's work include EEG and Brain-Computer Interfaces (22 papers), Blind Source Separation Techniques (13 papers) and Brain Tumor Detection and Classification (8 papers). Mohammad Zavid Parvez is often cited by papers focused on EEG and Brain-Computer Interfaces (22 papers), Blind Source Separation Techniques (13 papers) and Brain Tumor Detection and Classification (8 papers). Mohammad Zavid Parvez collaborates with scholars based in Bangladesh, Australia and United States. Mohammad Zavid Parvez's co-authors include Manoranjan Paul, Anisur Rahman, Mahmudul Hasan, Tasmi Tamanna, Ickjai Lee, Md Tanzim Reza, Mohammed Kaosar, Jia Uddin, Mohammad Shorif Uddin and Kyriaki Kalimeri and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, Neurocomputing and Chaos Solitons & Fractals.

In The Last Decade

Mohammad Zavid Parvez

42 papers receiving 934 citations

Hit Papers

CoroDet: A deep learning ... 2020 2026 2022 2024 2020 100 200 300
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.

  1. CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images
    2020 322 citations Mahmudul Hasan, Anisur Rahman et al. Chaos Solitons & Fractals profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Zavid Parvez Bangladesh 14 375 369 348 184 163 46 982
Palani Thanaraj Krishnan India 14 177 0.5× 251 0.7× 358 1.0× 106 0.6× 141 0.9× 39 939
Biao Jie China 22 835 2.2× 248 0.7× 383 1.1× 65 0.4× 248 1.5× 62 1.4k
Devon Hjelm United States 6 456 1.2× 342 0.9× 252 0.7× 75 0.4× 59 0.4× 11 945
T. Sunil Kumar India 11 190 0.5× 209 0.6× 141 0.4× 127 0.7× 56 0.3× 35 528
Mohammad-Parsa Hosseini United States 11 457 1.2× 110 0.3× 53 0.2× 146 0.8× 48 0.3× 14 766
María García Spain 19 378 1.0× 70 0.2× 674 1.9× 37 0.2× 49 0.3× 46 1.3k
Junjie Chen China 17 557 1.5× 105 0.3× 110 0.3× 124 0.7× 62 0.4× 81 933
Lasitha Vidyaratne United States 9 223 0.6× 121 0.3× 112 0.3× 137 0.7× 126 0.8× 31 566
R. Chaves Spain 15 198 0.5× 280 0.8× 153 0.4× 45 0.2× 400 2.5× 29 1.0k
Sang‐Woong Lee South Korea 10 69 0.2× 232 0.6× 116 0.3× 37 0.2× 91 0.6× 19 519

Countries citing papers authored by Mohammad Zavid Parvez

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Zavid Parvez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Zavid Parvez

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

All Works

20 of 20 papers shown
1.
Rahman, Md Geaur, Anisur Rahman, Mohammad Zavid Parvez, et al.. (2025). ADeepWeeD: An adaptive deep learning framework for weed species classification. Artificial Intelligence in Agriculture. 15(4). 590–609. 1 indexed citations
2.
Parvez, Mohammad Zavid, et al.. (2024). Explainable SE-MobileNet for Pneumonia detection integrated with robustness assessment using adversarial examples. Smart Health. 33. 100500–100500.
3.
Aboutorab, Hamed, Arash Mahboubi, Yansong Gao, et al.. (2024). Agriculture 4.0 and beyond: Evaluating cyber threat intelligence sources and techniques in smart farming ecosystems. Computers & Security. 140. 103754–103754. 24 indexed citations
4.
Reza, Md Tanzim, et al.. (2023). Improving Non-Invasive Brain Tumor Categorization using Transformers on MRI Data. 1 indexed citations
5.
Reza, Md Tanzim, et al.. (2022). Effectiveness of Federated Learning and CNN Ensemble Architectures for Identifying Brain Tumors Using MRI Images. Neural Processing Letters. 55(4). 3779–3809. 63 indexed citations
6.
Sultana, Abida, et al.. (2021). DFCatcher: A Deep CNN Model to Identify Deepfake Face Images. 545–550. 1 indexed citations
7.
Uddin, Mohammad Shorif, et al.. (2021). A squeeze and excitation ResNeXt-based deep learning model for Bangla handwritten compound character recognition. Journal of King Saud University - Computer and Information Sciences. 34(6). 3356–3364. 24 indexed citations
8.
Parvez, Mohammad Zavid, et al.. (2021). Multi-Stage Optimization of Deep Learning Model to Detect Thoracic Complications. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 3000–3005. 2 indexed citations
9.
Tamanna, Tasmi, et al.. (2021). Predicting seizure onset based on time-frequency analysis of EEG signals. Chaos Solitons & Fractals. 145. 110796–110796. 18 indexed citations
10.
11.
Tamanna, Tasmi, et al.. (2020). Consumer Behavior Analysis using EEG Signals for Neuromarketing Application. 2061–2066. 11 indexed citations
12.
Hasan, Mahmudul, et al.. (2020). CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images. Chaos Solitons & Fractals. 142. 110495–110495. 322 indexed citations breakdown →
13.
14.
Reza, Md Tanzim, et al.. (2020). Semantic Segmentation of Brain Tumor from 3D Structural MRI Using U-Net Autoencoder. 137–142. 5 indexed citations
15.
16.
Rahman, Anisur, et al.. (2020). Detection of Brain Tumor and Identification of Tumor Region Using Deep Neural Network On FMRI Images. 3. 124–130. 2 indexed citations
17.
Parvez, Mohammad Zavid, et al.. (2020). Prediction of Epileptic Seizures using Support Vector Machine and Regularization. 2020 IEEE Region 10 Symposium (TENSYMP). 1217–1220. 6 indexed citations
18.
Parvez, Mohammad Zavid, et al.. (2019). Recognition of emotional states using EEG signals based on time-frequency analysis and SVM classifier. International Journal of Electrical and Computer Engineering (IJECE). 9(2). 1012–1012. 49 indexed citations
19.
Parvez, Mohammad Zavid, Manoranjan Paul, & Michael Antolovich. (2015). Detection of Pre-stage of Epileptic Seizure by Exploiting Temporal Correlation of EMD Decomposed EEG Signals. Charles Sturt University Research Output (CRO). 4(2). 110–116. 11 indexed citations
20.
Parvez, Mohammad Zavid & Manoranjan Paul. (2013). Classification of Ictal and Interictal EEG Signals. 5 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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