Mohammed Moshiul Hoque

3.5k total citations
141 papers, 1.7k citations indexed

About

Mohammed Moshiul Hoque is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Mohammed Moshiul Hoque has authored 141 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Artificial Intelligence, 33 papers in Computer Vision and Pattern Recognition and 29 papers in Social Psychology. Recurrent topics in Mohammed Moshiul Hoque's work include Topic Modeling (29 papers), Natural Language Processing Techniques (22 papers) and Sentiment Analysis and Opinion Mining (21 papers). Mohammed Moshiul Hoque is often cited by papers focused on Topic Modeling (29 papers), Natural Language Processing Techniques (22 papers) and Sentiment Analysis and Opinion Mining (21 papers). Mohammed Moshiul Hoque collaborates with scholars based in Bangladesh, United Kingdom and Japan. Mohammed Moshiul Hoque's co-authors include Rosalind W. Picard, Oswaldo Castro, Omar Sharif, Iqbal H. Sarker, Nazmul Siddique, Matthieu Courgeon, Bilge Mutlu, Jean‐Claude Martin, Tawfeeq Alsanoosy and Eftekhar Hossain and has published in prestigious journals such as Blood, Expert Systems with Applications and IEEE Access.

In The Last Decade

Mohammed Moshiul Hoque

121 papers receiving 1.6k citations

Peers

Mohammed Moshiul Hoque

CVPR

GENET

ECP

Kenji Hashimoto Japan

Andrew Head United States

Inayat Khan Pakistan

Newton Howard United States

Martin Cooper France

Paul Hoffmann United States

Míriam Antón‐Rodríguez Spain

John Patterson United States

Franz J. Király Germany

Annika Wærn Sweden

Kenji Hashimoto Japan

Mohammed Moshiul Hoque

183 ×0.3

272 ×1.0

184 ×0.7

CVPR

64 ×0.3

GENET

77 ×0.4

ECP

Citations per year, relative to Mohammed Moshiul Hoque Mohammed Moshiul Hoque (= 1×) peers Kenji Hashimoto

Countries citing papers authored by Mohammed Moshiul Hoque

Since Specialization

Citations

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

Fields of papers citing papers by Mohammed Moshiul Hoque

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed Moshiul Hoque. 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 Mohammed Moshiul Hoque. The network helps show where Mohammed Moshiul Hoque may publish in the future.

Co-authorship network of co-authors of Mohammed Moshiul Hoque

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

All Works

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20 of 20 papers shown

Hoque, Mohammed Moshiul, et al.. (2026). MulMoSenT: Multimodal sentiment analysis for a low-resource language using textual-visual cross-attention and fusion. Information Fusion. 131. 104129–104129.

Hossain, Eftekhar, Omar Sharif, Mohammed Moshiul Hoque, & Sarah Masud Preum. (2024). Align before Attend: Aligning Visual and Textual Features for Multimodal Hateful Content Detection. 162–174.

Hoque, Mohammed Moshiul, et al.. (2024). SemanticCuetSync at ArAIEval Shared Task: Detecting Propagandistic Spans with Persuasion Techniques Identification using Pre-trained Transformers. 518–523.

Hoque, Mohammed Moshiul, et al.. (2024). AraCovTexFinder: Leveraging the transformer-based language model for Arabic COVID-19 text identification. Engineering Applications of Artificial Intelligence. 133. 107987–107987. 13 indexed citations

Hossain, Eftekhar, et al.. (2024). Enhancing image caption generation through context-aware attention mechanism. Heliyon. 10(17). e36272–e36272. 2 indexed citations

Hoque, Mohammed Moshiul, et al.. (2024). AVaTER: Fusing Audio, Visual, and Textual Modalities Using Cross-Modal Attention for Emotion Recognition. Sensors. 24(18). 5862–5862. 2 indexed citations

Hoque, Mohammed Moshiul, et al.. (2023). An empirical framework for detecting speaking modes using ensemble classifier. Multimedia Tools and Applications. 83(1). 2349–2382. 5 indexed citations

Hoque, Mohammed Moshiul, et al.. (2023). CovTiNet: Covid text identification network using attention-based positional embedding feature fusion. Neural Computing and Applications. 35(18). 13503–13527. 17 indexed citations

Hoque, Mohammed Moshiul, et al.. (2023). Leveraging the meta-embedding for text classification in a resource-constrained language. Engineering Applications of Artificial Intelligence. 124. 106586–106586. 23 indexed citations

10.

Hoque, Mohammed Moshiul, et al.. (2023). TEmoX: Classification of Textual Emotion Using Ensemble of Transformers. IEEE Access. 11. 109803–109818. 6 indexed citations

11.

Hossain, Eftekhar, Mohammed Moshiul Hoque, Enamul Hoque, & Md. Saiful Islam. (2022). A Deep Attentive Multimodal Learning Approach for Disaster Identification From Social Media Posts. IEEE Access. 10. 46538–46551. 12 indexed citations

12.

Iqbal, Md Asif, et al.. (2022). BEmoC: A Corpus for Identifying Emotion in Bengali Texts. SN Computer Science. 3(2). 135–135. 21 indexed citations

13.

Sharif, Omar, et al.. (2021). Classification of Textual Sentiment Using Ensemble Technique. SN Computer Science. 3(1). 18 indexed citations

14.

Sharif, Omar, et al.. (2021). Multi-class Textual Emotion Categorization using Ensemble of Convolutional and Recurrent Neural Network. SN Computer Science. 3(1). 9 indexed citations

15.

Sharmin, Shayla, Mohammed Moshiul Hoque, S. M. Riazul Islam, Md. Fazlul Kader, & Iqbal H. Sarker. (2021). Development of Duplex Eye Contact Framework for Human-Robot Inter Communication. IEEE Access. 9. 54435–54456. 5 indexed citations

16.

Sharif, Omar, et al.. (2020). Detecting Suspicious Texts Using Machine Learning Techniques. Applied Sciences. 10(18). 6527–6527. 27 indexed citations

17.

Sharif, Omar, Mohammed Moshiul Hoque, & Eftekhar Hossain. (2019). Sentiment Analysis of Bengali Texts on Online Restaurant Reviews Using Multinomial Naïve Bayes. 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT). 1–6. 40 indexed citations

18.

Hoque, Mohammed Moshiul, et al.. (2017). A Text-Based Chat System Embodied with an Expressive Agent. Advances in Human-Computer Interaction. 2017. 1–14. 2 indexed citations

19.

Das, Dipankar, Mohammed Moshiul Hoque, Yoshinori Kobayashi, & Yoshinori Kuno. (2013). Attention control system considering the target person's attention level. Human-Robot Interaction. 111–112. 4 indexed citations

20.

Haque, Mohammad Ariful, et al.. (2002). APPLICABILITY OF THE BEND DEVELOPMENT THEORY IN NATURAL ALLUVIAL RIVERS. 国际泥沙研究：英文版. 211–219. 2 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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