Searched for: subject%3A%22GANs%22
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van Os, Sven (author)
Nowcasting high-intensity precipitation is crucial for emergency services and municipalities when making weather-dependent decisions. This research implements and trains a deep generative model for nowcasting using a cleaned precipitation radar composite dataset spanning 15 years, with a 5-minute temporal and 1 km spatial resolution.<br/><br/>We...
master thesis 2024
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Taklimi, Sam (author)
The objective of this project is to train a model that transforms a tree with its foliage into only its branch structure. This is achieved by employing machine-learning techniques, specifically Generative Adverserial Networks (GANs). By utilizing the proposed method, a predictive model is built that automatically minimizes its own error function...
bachelor thesis 2024
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Yang, Chenyang (author), Sun, Jianwen (author), Zhang, Yulong (author), Tang, Jingya (author), Liu, Zizheng (author), Zhan, Teng (author), Wang, Dian-Bing (author), Zhang, Kouchi (author), Liu, Zewen (author), Zhang, Xian-En (author)
The COVID-19 pandemic has highlighted the need for rapid and sensitive detection of SARS-CoV-2. Here, we report an ultrasensitive SARS-CoV-2 immunosensor by integration of an AlGaN/GaN high-electron-mobility transistor (HEMT) and anti-SARS-CoV-2 spike protein antibody. The AlGaN/GaN HEMT immunosensor has demonstrated the capability to detect...
journal article 2024
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Zhao, Z. (author), Huang, J. (author), Chen, Lydia Y. (author), Roos, S. (author)
Generative Adversarial Networks (GANs) are increasingly adopted by the industry to synthesize realistic images using competing generator and discriminator neural networks. Due to data not being centrally available, Multi-Discriminator (MD)-GANs training frameworks employ multiple discriminators that have direct access to the real data....
conference paper 2024
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Pan, Jing (author)
GaN transistors have advantages over conventional Si MOSFETs, such as lower on-resistance, lower parasitic capacitance, higher break-down voltage, etc. However, due to the lack of the body diode, when GaN transistors conduct reverse current during dead time, the source-drain voltage (VSD) can be very large (up to 4-5 V, depending on the output...
master thesis 2023
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ZHUANG, XUANYU (author)
In the task of music style transfer, the symbolic music representation based on Musical Instrument Digital Interface (MIDI) files has always been a popular research medium. By using such representation, some mature models for image style transfer can also be applied to this scenario, such as Cycle-consistent Generative Adversarial Networks ...
master thesis 2023
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Sharma, Anirvin (author)
Image data augmentation has been regarded as a reliable and effective way to increase the data available for training. With the advent and rise of Generative AI, generative data augmentation has been shown to realize even better gains in performance for downstream tasks. However, these performance gains are often the cause of "extra information"...
master thesis 2023
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Xie, yukun (author)
Research pertaining to end-use water analysis plays a pivotal role in enabling local communities to enhance their management of pipelines, water resources, and associated policies. Nowadays, various end-use models have been developed based on diverse databases and measurements. Nonetheless, a predominant drawback prevalent in most of these...
master thesis 2023
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HADJIGEORGIOU, MARIOS (author)
Federated Learning (FL) is widely favoured in the training of machine learning models due to its privacy-preserving and data diversity benefits. In this research paper, we investigate an extension of FL referred to as Personalized Federated Learning (PFL) for the purpose of training diffusion models. We explore the personalization technique of...
bachelor thesis 2023
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Akdemir, Rauf (author)
As privacy regulations (e.g. European General Data Protection Regulation) often prevent valuable flows of data between stakeholders, data synthesis can play a crucial role in sharing captured value in data sets without sharing personal details. Different attempts have been made at solving this problem with Generative Adversarial Networks (GAN)...
bachelor thesis 2023
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Singh, G.D. (author), Nemati, Hossein Mashad (author), Alavi, S.M. (author), de Vreede, L.C.N. (author)
This paper proposes a power amplifier (PA) correction technique to recover from load mismatch. It utilizes a main PA, two auxiliary PAs, and a coupler. By adjusting the input drive levels of the PAs it can recover the output power and to a great extent the efficiency of the main PA even when exposed to 2:1 VSWR mismatch conditions. When...
conference paper 2023
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Zhao, Z. (author), Birke, Robert (author), Chen, Lydia Y. (author)
Generative Adversarial Networks (GANs) are typically trained to synthesize data, from images and more recently tabular data, under the assumption of directly accessible training data. While learning image GANs on Federated Learning (FL) and Multi-Discriminator (MD) systems has just been demonstrated, it is unknown if tabular GANs can be learned...
conference paper 2023
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Chen, Minggang (author), Zhang, H. (author), Fan, Q. (author)
Silicon MOSFETs-based medium-power (&lt; 50W) Class-D amplifiers (CDAs) switching in the MHz range have gained popularity in recent years, which achieves better linearity thanks to a higher loop gain in the audio band while enabling the use of LC filters with higher cut-off frequencies. However, for high-power (&gt;100 W) CDAs, such switching...
conference paper 2023
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Ghavamipour, Ali Reza (author), Turkmen, Fatih (author), Wang, Rui (author), Liang, K. (author)
Synthetic data generation plays a crucial role in many areas where data is scarce and privacy/confidentiality is a significant concern. Generative Adversarial Networks (GANs), arguably one of the most widely used data synthesis techniques, allow for the training of a model (i.e., generator) that can generate real-looking data by playing a min...
conference paper 2023
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Zhao, Z. (author), Birke, Robert (author), Chen, Lydia Y. (author)
An alternative method for sharing knowledge while complying with strict data access regulations, such as the European General Data Protection Regulation (GDPR), is the emergence of synthetic tabular data. Mainstream table synthesizers utilize methodologies derived from Generative Adversarial Networks (GAN). Although several state-of-the-art ...
conference paper 2023
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Sharma, Bhawana (author), Sharma, Lokesh (author), Lal, C. (author), Roy, Satyabrata (author)
Internet of Things (IoT) applications are growing in popularity for being widely used in many real-world services. In an IoT ecosystem, many devices are connected with each other via internet, making IoT networks more vulnerable to various types of cyber attacks, thus a major concern in its deployment is network security and user privacy. To...
journal article 2023
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Franci, B. (author), Grammatico, S. (author)
Generative adversarial networks (GANs) are a class of generative models with two antagonistic neural networks: a generator and a discriminator. These two neural networks compete against each other through an adversarial process that can be modeled as a stochastic Nash equilibrium problem. Since the associated training process is challenging,...
journal article 2023
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Hua, Yuan (author), Lu, Qi (author), Li, Shuangmu (author), Zhao, Bo (author), Du, S. (author)
This brief presents a 48V-to-1V 10-level dual inductor hybrid converter (DIHC) containing 11 on-chip switches and an off-chip gallium nitride (GaN) switch. Thanks to the 10-level Dickson switched-capacitor (SC) circuit, most of the voltage stress will be taken over by off-chip capacitors, which reduces the voltage stress of each switch to 4.8...
journal article 2023
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Kemna, Mirko (author)
The goal of this work is to evaluate the aptness of generative adversarial networks (GANs) for use as surrogate reduced order fluid models. In contrast to previously published work, the focus is placed on analyzing the specific effect of adversarial training, by comparing GAN outcomes with those from an identical generator network trained...
master thesis 2022
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HUA, YUAN (author)
This thesis presents a 48V-to-1V 10-level dual inductor hybrid converter (DIHC) containing 11 on-chip switches and an off-chip Gallium Nitride (GaN) switch. Thanks to the 10-level Dickson switched-capacitor (SC) circuit, most of the voltage stress will be taken over by off-chip capacitors, which reduces the voltage stress of each switch to 4.8 V...
master thesis 2022
Searched for: subject%3A%22GANs%22
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