Women Researcher Award
Ayesha Banu
Chittagong University of Engineering and Technology (CUET), Bangladesh
| Ayesha Banu |
| Researcher |
Ayesha Banu |
| Affiliation |
Chittagong University of Engineering and Technology (CUET) |
| Country |
Bangladesh |
| Scopus ID |
60706667500 |
| Documents |
3 |
| Citations |
0 |
| h-index |
0 |
| Subject Area |
Computer Vision |
| Event |
Global CSE Awards |
Ayesha Banu is a researcher affiliated with Chittagong University of Engineering and Technology (CUET), Bangladesh, whose documented publications address computer vision and deep learning. Her recent work includes image deraining and protein secondary structure prediction, reflecting applications of neural architectures, generative models, attention mechanisms, and sequence modeling across computational research domains. [1] [2] [3]
Abstract
Ayesha Banu is affiliated with Chittagong University of Engineering and Technology (CUET), Bangladesh, and has documented research spanning computer vision and deep learning. Her publication record includes studies on single-image deraining using Atrous U-Net and generative adversarial networks, an attention-enhanced GAN approach for image restoration, and E2BNet, a hybrid ESM2-BiLSTM model for eight-state protein secondary structure prediction. These works examine neural architectures for visual restoration and computational sequence analysis, using established evaluation measures and benchmark datasets. The supplied Scopus information records three documents, zero citations, and an h-index of zero, providing a concise bibliographic snapshot for her current academic profile. [1] [2] [3]
Keywords
Women Researcher Award; Ayesha Banu; Computer Vision; Deep Learning; Image Deraining; Generative Adversarial Networks; Atrous U-Net; Attention Mechanisms; ESM2; BiLSTM; Protein Secondary Structure Prediction; CUET; Global CSE Awards.
Introduction
Computer vision research increasingly uses deep learning to address image restoration and recognition problems under challenging visual conditions. Banu’s documented studies include generative adversarial networks, U-Net variants, attention mechanisms, and learning architectures for image deraining, alongside a hybrid ESM2-BiLSTM model for protein structure prediction. These works demonstrate interdisciplinary computational methods. [1] [2] [3]
Research Profile
The available publication record identifies Ayesha Banu with Chittagong University of Engineering and Technology in Bangladesh. The supplied Scopus record lists three documents, zero citations, and an h-index of zero. Her stated subject area is Computer Vision, while publications also connect computer vision methods with broader deep learning and computational biology. [1] [2] [3]
Research Contributions
Banu’s documented contributions include research on single-image deraining using Atrous U-Net and GAN architectures, attention-enhanced GAN-based restoration, and hybrid deep learning for eight-state protein secondary structure prediction. These studies apply convolutional, generative, attention-based, and sequential models to structured prediction and image restoration problems, with quantitative evaluation reported in publications. [1] [2] [3]
Publications
Three publications are identified for this profile. The 2024 IEEE conference paper addresses single-image deraining with Atrous U-Net and GAN. Two 2026 Discover Applied Sciences articles examine attention-enhanced GAN deraining and the E2BNet architecture combining ESM2 with BiLSTM for protein secondary structure prediction. Each publication provides a documented scholarly contribution relevant to research. [1] [2] [3]
Research Impact
The documented research impact can be described through publication outputs and methods presented in the cited studies. The deraining research reports image-quality evaluation using metrics including PSNR and SSIM, while the E2BNet study evaluates Q8 protein secondary structure prediction across benchmark datasets. The supplied profile currently records zero citations and h-index zero. [1] [2] [3]
Award Suitability
For a Women Researcher Award profile, the available evidence provides a documented basis for considering research activity, publication record, institutional affiliation, and subject-area relevance. The three identified publications demonstrate engagement with computational methods. Final award eligibility or selection should be determined by Global CSE Awards criteria and submitted supporting evidence. [1] [2] [3]
Conclusion
Ayesha Banu’s documented publication record reflects research involving computer vision, deep learning, image restoration, generative adversarial networks, attention mechanisms, and protein sequence modeling. The supplied bibliographic information establishes three publications and a CUET affiliation. Together, these records provide a concise scholarly profile for academic recognition and further assessment under applicable criteria. [1] [2] [3]
External Links
References
- Droba, D. D., Banu, A., Sami, M. I., Hossain, R., & Chowdhury, M. (2026). Hybrid deep learning model (E2BNet) combining ESM2 and BiLSTM for 8-state protein secondary structure prediction. Discover Applied Sciences, 8, Article 681.
https://doi.org/10.1007/s42452-026-08615-z
- Banu, A., & Hossain, R. (2026). Attention-enhanced GAN for single image deraining. Discover Applied Sciences.
https://doi.org/10.1007/s42452-026-08519-y
- Banu, A., Anan, S., & Deb, K. (2024). Removing rain from single image using Atrous U-Net and GAN. In 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT). IEEE.
https://doi.org/10.1109/ICEEICT62016.2024.10534531