Frank Kulwa

1.1k total citations · 1 hit paper
25 papers, 765 citations indexed

About

Frank Kulwa is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Artificial Intelligence. According to data from OpenAlex, Frank Kulwa has authored 25 papers receiving a total of 765 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 9 papers in Biophysics and 8 papers in Artificial Intelligence. Recurrent topics in Frank Kulwa's work include Cell Image Analysis Techniques (8 papers), AI in cancer detection (7 papers) and EEG and Brain-Computer Interfaces (7 papers). Frank Kulwa is often cited by papers focused on Cell Image Analysis Techniques (8 papers), AI in cancer detection (7 papers) and EEG and Brain-Computer Interfaces (7 papers). Frank Kulwa collaborates with scholars based in China, United Kingdom and United States. Frank Kulwa's co-authors include Chen Li, Md Mamunur Rahaman, Yudong Yao, Xin Zhao, Shouliang Qi, Xiangchen Wu, Xiaoyan Li, Qian Wang, Xuemin Zhu and Qian Wang and has published in prestigious journals such as PLoS ONE, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Frank Kulwa

25 papers receiving 746 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.

DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques

2021 201 citations Md Mamunur Rahaman, Chen Li et al. Computers in Biology and Medicine profile →

Peers

Frank Kulwa

RNMI

CVPR

BIOPH

Haoyuan Chen China

Ali Mohammad Alqudah Jordan

Wanli Liu China

Vivek Kumar Singh United States

Adrián Colomer Spain

Xiaowei Ding China

Shekoofeh Azizi United States

Malaya Kumar Nath India

Samir S. Yadav India

Sertan Serte Cyprus

Haoyuan Chen China

Frank Kulwa

506 ×1.1

327 ×1.0

RNMI

253 ×1.2

CVPR

51 ×0.5

60 ×0.6

BIOPH

Citations per year, relative to Frank Kulwa Frank Kulwa (= 1×) peers Haoyuan Chen

Countries citing papers authored by Frank Kulwa

Since Specialization

Citations

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

Fields of papers citing papers by Frank Kulwa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank Kulwa

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Kulwa. A scholar is included among the top collaborators of Frank Kulwa 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 Frank Kulwa. Frank Kulwa 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

Kulwa, Frank, Mengtao Wang, Guanglin Li, et al.. (2025). A Novel sEMG-FMG Combined Sensor Fusion Approach Based on an Attention-Driven CNN for Dynamic Hand Gesture Recognition. IEEE Transactions on Instrumentation and Measurement. 74. 1–13. 3 indexed citations

Kulwa, Frank, et al.. (2025). A NMF-Based Non-Euclidean Adaptive Feature Extraction Scheme for Limb Motion Pattern Decoding in Pattern Recognition System. IEEE Transactions on Biomedical Engineering. 73(2). 742–755. 2 indexed citations

Kulwa, Frank, et al.. (2024). A robust feature adaptation approach against variation of muscle contraction forces for myoelectric pattern recognition-based gesture characterization. Biomedical Signal Processing and Control. 95. 106446–106446. 4 indexed citations

Igbe, Tobore, Abhishek Kandwal, Jingzhen Li, et al.. (2024). Exploring EEG Signals for Noninvasive Blood Glucose Monitoring in Prediabetes Diagnosis. IEEE Transactions on Instrumentation and Measurement. 73. 1–8. 1 indexed citations

Kulwa, Frank, et al.. (2024). Adapting Image Classification Adversarial Detection Methods for Traffic Sign Classification in Autonomous Vehicles: A Comparative Study. IEEE Transactions on Intelligent Transportation Systems. 25(11). 19046–19061. 4 indexed citations

Samuel, Oluwarotimi Williams, Mojisola Grace Asogbon, Frank Kulwa, et al.. (2024). An Efficient Deep Transfer Learning Network for Characterization of Stroke Patients’ Motor Execution from Multi-Channel EEG-Recordings. PubMed. 2024. 1–4. 1 indexed citations

Samuel, Oluwarotimi Williams, et al.. (2023). Enhanced Deep Transfer Learning Model based on Spatial-Temporal driven Scalograms for Precise Decoding of Motor Intent in Stroke Survivors. PubMed. 2023. 1–4. 1 indexed citations

Kulwa, Frank, Chen Li, Jinghua Zhang, et al.. (2022). A new pairwise deep learning feature for environmental microorganism image analysis. Environmental Science and Pollution Research. 29(34). 51909–51926. 43 indexed citations

Kulwa, Frank, Chen Li, Marcin Grzegorzek, et al.. (2022). Segmentation of weakly visible environmental microorganism images using pair-wise deep learning features. Biomedical Signal Processing and Control. 79. 104168–104168. 10 indexed citations

10.

Li, Zihan, Chen Li, Yudong Yao, et al.. (2021). EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks. PLoS ONE. 16(5). e0250631–e0250631. 12 indexed citations

11.

Ma, He, et al.. (2021). Breast Cancer Segmentation Methods: Current Status and Future Potentials. BioMed Research International. 2021(1). 9962109–9962109. 71 indexed citations

12.

Rahaman, Md Mamunur, Chen Li, Yudong Yao, et al.. (2021). DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques. Computers in Biology and Medicine. 136. 104649–104649. 201 indexed citations breakdown →

13.

Li, Chen, Frank Kulwa, Md Mamunur Rahaman, et al.. (2020). Foldover Features for Dynamic Object Behaviour Description in Microscopic Videos. IEEE Access. 8. 114519–114540. 12 indexed citations

14.

Zhang, Jinghua, Chen Li, Frank Kulwa, et al.. (2020). A Multiscale CNN‐CRF Framework for Environmental Microorganism Image Segmentation. BioMed Research International. 2020(1). 4621403–4621403. 20 indexed citations

15.

Rahaman, Md Mamunur, Chen Li, Yudong Yao, et al.. (2020). Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches. Journal of X-Ray Science and Technology. 28(5). 821–839. 212 indexed citations

16.

Li, Chen, Frank Kulwa, Jinghua Zhang, et al.. (2020). A Review of Clustering Methods in Microorganism Image Analysis. Advances in intelligent systems and computing. 13–25. 22 indexed citations

17.

Sun, Changhao, Chen Li, Jinghua Zhang, Frank Kulwa, & Xiaoyan Li. (2020). Hierarchical conditional random field model for multi‐object segmentation in gastric histopathology images. Electronics Letters. 56(15). 750–753. 9 indexed citations

18.

Sun, Changhao, Chen Li, Jinghua Zhang, et al.. (2020). Gastric histopathology image segmentation using a hierarchical conditional random field. Journal of Applied Biomedicine. 40(4). 1535–1555. 44 indexed citations

19.

Xu, Hao, Chen Li, Md Mamunur Rahaman, et al.. (2020). An Enhanced Framework of Generative Adversarial Networks (EF-GANs) for Environmental Microorganism Image Augmentation With Limited Rotation-Invariant Training Data. IEEE Access. 8. 187455–187469. 28 indexed citations

20.

Kulwa, Frank, Chen Li, Xin Zhao, et al.. (2019). A State-of-the-Art Survey for Microorganism Image Segmentation Methods and Future Potential. IEEE Access. 7. 100243–100269. 47 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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