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publications
A highly birefringent negative chromatic dispersion photonic crystal fibre for long-haul transmission: design and analysis
Published in Results in Optics, 2022
The study presents a circular photonic crystal fiber (CPCF) operating from 1350 nm to 1650 nm, with high negative dispersion at 1.55 µm, high birefringence, and low loss, ideal for broadband dispersion compensation, supercontinuum generation, polarization maintenance, and sensing.
Recommended citation: Arhinful, F., Akowuah, E.K., Danlard, I. and Dede, A., 2022. A highly birefringent negative chromatic dispersion photonic crystal fibre for long-haul transmission: design and analysis. Results in Optics, 9, p.100325.
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Design and numerical analysis of a circular SPR based PCF biosensor for aqueous environments
Published in Results in Optics, 2023
This paper presents a circular photonic crystal fiber biosensor for aqueous environments, using surface plasmon resonance for high sensitivity and resolution in a refractive index range of 1.30 to 1.44.
Recommended citation: Opoku, G., Danlard, I., Dede, A. and Akowuah, E.K., 2023. Design and numerical analysis of a circular SPR based PCF biosensor for aqueous environments. Results in Optics, 12, p.100432.
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Extremely randomised trees machine learning model for electricity theft detection
Published in Machine Learning with Applications, 2023
This research introduces an efficient model for detecting electricity theft using an extremely randomized trees classifier, improved by SMOTE Tomek sampling and hyperparameter optimization, achieving high accuracy in identifying fraudulent consumption.
Recommended citation: Appiah, S.Y., Akowuah, E.K., Ikpo, V.C. and Dede, A., 2023. Extremely randomised trees machine learning model for electricity theft detection. Machine Learning with Applications, 12, p.100458.
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Design and analysis of a hexagonal circular photonic crystal fibre with ultra-high negative dispersion and low confinement loss
Published in Results in Optics, 2023
This paper discusses a Hexagonal Circular Photonic Crystal Fiber (HC-PCF) with ultra-high negative dispersion, high birefringence, and low confinement loss, suitable for long-range telecommunications and optical sensing.
Recommended citation: N-yorbe, J.N., Akowuah, E.K., Danlard, I., Dede, A. and Haxha, S., 2023. Design and analysis of a hexagonal circular photonic crystal fibre with ultra-high negative dispersion and low confinement loss. Results in Optics, 12, p.100488.
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Digital backpropagation based on binary logarithmic step size distribution for fibre non-linearity compensation
Published in The Journal of Engineering, 2023
A proposed low-complexity digital backpropagation method using a binary logarithmic step size achieves significant performance improvements in high-data-rate optical transmission systems, extending transmission distances and reducing computational costs.
Recommended citation: Dede, A., Akowuah, E.K. and Haxha, S., 2023. Digital backpropagation based on binary logarithmic step size distribution for fibre non‐linearity compensation. The Journal of Engineering, 2023(12), p.e12340.
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Wavelet-Based Feature Extraction for Efficient High-Resolution Image Classification
Published in Engineering Reports, 2025
This paper presents WaveNet, a method that improves the classification accuracy of high-resolution images in CNNs using wavelet-domain inputs and a wavelet-adaptive efficient channel attention module, while reducing computational complexity.
Recommended citation: Dede, A., Nunoo‐Mensah, H., Akowuah, E.K., Boateng, K.O., Adjei, P.E., Acheampong, F.A., Acquah, I. and Kponyo, J.J., 2025. Wavelet‐Based Feature Extraction for Efficient High‐Resolution Image Classification. Engineering Reports, 7(2), p.e70027.
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Deep learning for efficient high-resolution image processing: A systematic review
Published in Intelligent Systems with Applications, 2025
The paper reviews deep learning techniques that enhance the efficiency of high-resolution image processing, exploring various models and their applications while addressing performance challenges and suggesting future research directions.
Recommended citation: Dede, A., Nunoo-Mensah, H., Tchao, E.T., Agbemenu, A.S., Adjei, P.E., Acheampong, F.A. and Kponyo, J.J., 2025. Deep learning for efficient high-resolution image processing: A systematic review. Intelligent Systems with Applications, p.200505.
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talks
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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