Cam-Hao Hua

1.6k total citations · 1 hit paper
36 papers, 1.1k citations indexed

About

Cam-Hao Hua is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Cam-Hao Hua has authored 36 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 7 papers in Biomedical Engineering. Recurrent topics in Cam-Hao Hua's work include Human Pose and Action Recognition (9 papers), Wireless Signal Modulation Classification (8 papers) and Gait Recognition and Analysis (6 papers). Cam-Hao Hua is often cited by papers focused on Human Pose and Action Recognition (9 papers), Wireless Signal Modulation Classification (8 papers) and Gait Recognition and Analysis (6 papers). Cam-Hao Hua collaborates with scholars based in South Korea, Kazakhstan and Vietnam. Cam-Hao Hua's co-authors include Thien Huynh‐The, Dong‐Seong Kim, Quoc‐Viet Pham, Sungyoung Lee, Nguyen Anh Tu, Jaehun Bang, Van‐Sang Doan, Mugahed A. Al–antari, Sung‐Ho Bae and Toan-Van Nguyen and has published in prestigious journals such as IEEE Access, Sensors and Information Sciences.

In The Last Decade

Cam-Hao Hua

35 papers receiving 1.1k citations

Hit Papers

MCNet: An Efficient CNN Architecture for Robust Automatic... 2020 2026 2022 2024 2020 50 100 150 200
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. MCNet: An Efficient CNN Architecture for Robust Automatic Modulation Classification
    2020 238 citations Thien Huynh‐The, Cam-Hao Hua et al. profile →

Peers

Cam-Hao Hua
Jamshid Shanbehzadeh Iran
Claudia Loy United Kingdom
Prabin Kumar Bora India
Mihir Narayan Mohanty India
Mohammad Haghighat United States
Yuan He China
Xiang Bai China
Alaaeldin El-Nouby Sweden
Byung Cheol Song South Korea
Akio Kosaka United States
Jamshid Shanbehzadeh Iran
Cam-Hao Hua
Citations per year, relative to Cam-Hao Hua Cam-Hao Hua (= 1×) peers Jamshid Shanbehzadeh

Countries citing papers authored by Cam-Hao Hua

Since Specialization
Citations

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

Fields of papers citing papers by Cam-Hao Hua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cam-Hao Hua. 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 Cam-Hao Hua. The network helps show where Cam-Hao Hua may publish in the future.

Co-authorship network of co-authors of Cam-Hao Hua

This figure shows the co-authorship network connecting the top 25 collaborators of Cam-Hao Hua. A scholar is included among the top collaborators of Cam-Hao Hua 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 Cam-Hao Hua. Cam-Hao Hua 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.
Yoon, Minjae, Taeho Hur, Sang‐Ho Jo, et al.. (2025). Self-Monitoring of Blood Pressure and Feedback via Mobile App in Treatment of Uncontrolled Hypertension: The SMART-BP Randomized Clinical Trial. Mayo Clinic Proceedings. 100(5). 840–853. 1 indexed citations
2.
Yoon, Minjae, Jin Joo Park, Taeho Hur, et al.. (2023). Application and Potential of Artificial Intelligence in Heart Failure: Past, Present, and Future. PubMed. 6(1). 11–11. 16 indexed citations
3.
4.
Razzaq, Muhammad Asif, Jamil Hussain, Jaehun Bang, et al.. (2023). A Hybrid Multimodal Emotion Recognition Framework for UX Evaluation Using Generalized Mixture Functions. Sensors. 23(9). 4373–4373. 15 indexed citations
5.
Nguyen, T. D., et al.. (2023). CLEB: A Continual Learning Energy Bidding Framework For An Energy Market Bidding Application. 46–53. 1 indexed citations
6.
Huynh‐The, Thien, Van‐Sang Doan, Cam-Hao Hua, et al.. (2021). Accurate LPI Radar Waveform Recognition With CWD-TFA for Deep Convolutional Network. IEEE Wireless Communications Letters. 10(8). 1638–1642. 80 indexed citations
7.
Huynh‐The, Thien, Cam-Hao Hua, Nguyen Anh Tu, & Dong‐Seong Kim. (2020). Space-Time Skeletal Analysis with Jointly Dual-Stream ConvNet for Action Recognition. 1–7. 1 indexed citations
8.
Huynh‐The, Thien, Cam-Hao Hua, Nguyen Anh Tu, & Dong‐Seong Kim. (2020). Physical Activity Recognition With Statistical-Deep Fusion Model Using Multiple Sensory Data for Smart Health. IEEE Internet of Things Journal. 8(3). 1533–1543. 55 indexed citations
9.
Huynh‐The, Thien, Cam-Hao Hua, Nguyen Anh Tu, & Dong‐Seong Kim. (2020). Learning Geometric Features with Dual–stream CNN for 3D Action Recognition. 2353–2357. 12 indexed citations
10.
Hua, Cam-Hao, Kiyoung Kim, Thien Huynh‐The, et al.. (2020). Convolutional Network With Twofold Feature Augmentation for Diabetic Retinopathy Recognition From Multi-Modal Images. IEEE Journal of Biomedical and Health Informatics. 25(7). 2686–2697. 41 indexed citations
11.
Hua, Cam-Hao, Thien Huynh‐The, Hyunseok Seo, & Sungyoung Lee. (2020). Convolutional Network with Densely Backward Attention for Facial Expression Recognition. 1–6. 11 indexed citations
12.
Al–antari, Mugahed A., Cam-Hao Hua, Jaehun Bang, & Sungyoung Lee. (2020). “Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images”. Applied Intelligence. 51(5). 2890–2907. 89 indexed citations
13.
Huynh‐The, Thien, Cam-Hao Hua, Jae-Woo Kim, Seung-Hwan Kim, & Dong‐Seong Kim. (2020). Exploiting a low-cost CNN with skip connection for robust automatic modulation classification. 1–6. 28 indexed citations
14.
Hua, Cam-Hao, Thien Huynh‐The, Sung‐Ho Bae, & Sungyoung Lee. (2020). Cross-Attentional Bracket-shaped Convolutional Network for semantic image segmentation. Information Sciences. 539. 277–294. 22 indexed citations
15.
Hua, Cam-Hao, Thien Huynh‐The, Kiyoung Kim, et al.. (2019). Bimodal learning via trilogy of skip-connection deep networks for diabetic retinopathy risk progression identification. International Journal of Medical Informatics. 132. 103926–103926. 42 indexed citations
16.
Huynh‐The, Thien, Cam-Hao Hua, Nguyen Anh Tu, & Dong‐Seong Kim. (2019). Robust Image Watermarking Framework Powered by Convolutional Encoder-Decoder Network. 1–7. 9 indexed citations
17.
Huynh‐The, Thien, et al.. (2019). Image representation of pose-transition feature for 3D skeleton-based action recognition. Information Sciences. 513. 112–126. 66 indexed citations
18.
Huynh‐The, Thien, Cam-Hao Hua, Nguyen Anh Tu, & Dong‐Seong Kim. (2019). Locally Statistical Dual-Mode Background Subtraction Approach. IEEE Access. 7. 9769–9782. 9 indexed citations
19.
Hua, Cam-Hao, Thien Huynh‐The, & Sungyoung Lee. (2018). Convolutional Networks with Bracket-Style Decoder for Semantic Scene Segmentation. 2980–2985. 17 indexed citations
20.
Huynh‐The, Thien, Cam-Hao Hua, Nguyen Anh Tu, et al.. (2017). Selective bit embedding scheme for robust blind color image watermarking. Information Sciences. 426. 1–18. 65 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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