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Baris Yigin and Metin Celik
In recent years, advanced methods and smart solutions have been investigated for the safe, secure, and environmentally friendly operation of ships. Since data acquisition capabilities have improved, data processing has become of great importance for ship...
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Xiaoou Li
This paper tackles the challenge of time series forecasting in the presence of missing data. Traditional methods often struggle with such data, which leads to inaccurate predictions. We propose a novel framework that combines the strengths of Generative ...
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Mohammad Alhumaid and Ayman G. Fayoumi
Paranasal sinus pathologies, particularly those affecting the maxillary sinuses, pose significant challenges in diagnosis and treatment due to the complex anatomical structures and diverse disease manifestations. The aim of this study is to investigate t...
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Ku Muhammad Naim Ku Khalif, Woo Chaw Seng, Alexander Gegov, Ahmad Syafadhli Abu Bakar and Nur Adibah Shahrul
Convolutional Neural Networks (CNNs) have garnered significant utilisation within automated image classification systems. CNNs possess the ability to leverage the spatial and temporal correlations inherent in a dataset. This study delves into the use of ...
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Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
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Yibo He, Kah Phooi Seng and Li Minn Ang
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Maryam Omar, Hafeez Ur Rehman, Omar Bin Samin, Moutaz Alazab, Gianfranco Politano and Alfredo Benso
Text-to-image synthesis is one of the most critical and challenging problems of generative modeling. It is of substantial importance in the area of automatic learning, especially for image creation, modification, analysis and optimization. A number of wo...
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Fengxu Guan, Siqi Lu, Haitao Lai and Xue Du
Underwater optical imaging devices are often affected by the complex underwater environment and the characteristics of the water column, which leads to serious degradation and distortion of the images they capture. Deep learning-based underwater image en...
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Hua Zhang, Muwei Wang, Lingjun Zhang, Yifan Wu and Yizhang Luo
Global photographic aesthetic image generation aims to ensure that images generated by generative adversarial networks (GANs) contain semantic information and have global aesthetic feelings. Existing image aesthetic generation algorithms are still in the...
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Mohammad Alauthman, Ahmad Al-qerem, Bilal Sowan, Ayoub Alsarhan, Mohammed Eshtay, Amjad Aldweesh and Nauman Aslam
Developing an effective classification model in the medical field is challenging due to limited datasets. To address this issue, this study proposes using a generative adversarial network (GAN) as a data-augmentation technique. The research aims to enhan...
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