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Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
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Eduardo Morales-Vargas, Hayde Peregrina-Barreto, Rita Q. Fuentes-Aguilar, Juan Pablo Padilla-Martinez, Wendy Argelia Garcia-Suastegui and Julio C. Ramirez-San-Juan
Microvasculature analysis is an important task in the medical field due to its various applications. It has been used for the diagnosis and threat of diseases in fields such as ophthalmology, dermatology, and neurology by measuring relative blood flow or...
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Georgios Karantaidis and Constantine Kotropoulos
The detection of computer-generated (CG) multimedia content has become of utmost importance due to the advances in digital image processing and computer graphics. Realistic CG images could be used for fraudulent purposes due to the deceiving recognition ...
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Shihao Ma, Jiao Wu, Zhijun Zhang and Yala Tong
Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster d...
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Miniyenkosi Ngcukayitobi, Lagouge Kwanda Tartibu and Flávio Bannwart
Waste heat recovery stands out as a promising technique for tackling both energy shortages and environmental pollution. Currently, this valuable resource, generated through processes like fuel combustion or chemical reactions, is often dissipated into th...
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Dongxue Zhao, Yingli Cao, Jinpeng Li, Qiang Cao, Jinxuan Li, Fuxu Guo, Shuai Feng and Tongyu Xu
Leaf blast is recognized as one of the most devastating diseases affecting rice production in the world, seriously threatening rice yield. Therefore, early detection of leaf blast is extremely important to limit the spread and propagation of the disease....
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Ashir Javeed, Muhammad Asim Saleem, Ana Luiza Dallora, Liaqat Ali, Johan Sanmartin Berglund and Peter Anderberg
Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality. We developed a clini...
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Xiaoping Huang, Yujian Zhou and Yajun Du
In recent years, there has been rapid development in machine learning for solving artificial intelligence tasks in various fields, including translation, speech, and image processing. These AI tasks are often interconnected rather than independent. One s...
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Ran Chen, Jing Zhao, Xueqi Yao, Sijia Jiang, Yingting He, Bei Bao, Xiaomin Luo, Shuhan Xu and Chenxi Wang
Generative Adversarial Networks (GANs) possess a significant ability to generate novel images that adhere to specific guidelines across multiple domains. GAN-assisted generative design is a design method that can automatically generate design schemes wit...
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Jialin Zhang, Mairidan Wushouer, Gulanbaier Tuerhong and Hanfang Wang
Emotional speech synthesis is an important branch of human?computer interaction technology that aims to generate emotionally expressive and comprehensible speech based on the input text. With the rapid development of speech synthesis technology based on ...
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