Searched for: subject%3A%22adversarial%22
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Cisneros Acevedo, Daniel (author)
Recent advancements in deep learning for aircraft engine fault detection have been predominantly focused on research using simulated datasets. Despite significant progress, the gap between simulated and real-world data underscores a pressing need for models that are more applicable and adaptable to the aerospace industry. This discrepancy stems...
master thesis 2024
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Pigmans, Max (author)
Most of the adversarial attacks suitable for attacking decision tree ensembles work by doing multiple local searches from randomly selected starting points, around the to be attacked victim. In this thesis we investigate the impact of these starting points on the performance of the attack, and find that the starting points significantly impact...
master thesis 2024
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Xia, W. (author), Huang, Hanyue (author), Duque, Edgar Mauricio Salazar (author), Shengren, H. (author), Palensky, P. (author), Vergara Barrios, P.P. (author)
Residential load profiles (RLPs) play an increasingly important role in the optimal operation and planning of distribution systems, particularly with the rising integration of low-carbon energy resources such as PV systems, electric vehicles, small-scale batteries, etc. Despite the prevalence of various data-driven models for generating...
journal article 2024
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Gao, Yuxing (author)
The rapid advancement in autonomous driving technology underscores the importance of studying the fragility of perception systems in autonomous vehicles, particularly due to their profound impact on public transportation safety. These systems are of paramount importance due to their direct impact on the lives of passengers and pedestrians....
master thesis 2023
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Yap, Li-Toong (author)
Site analysis to determine the loads experienced by wind turbines based on site-specific environmental conditions is typically done using either coupled aero-servo-elastic simulations for onshore wind turbines or coupled aero-servo-hydroelastic simulations in the case of offshore wind turbines. These simulations become computationally expensive...
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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Campos Montero, Fabian (author)
This thesis introduces a novel Generative Adversarial Network application called SchemaGAN, which has been adapted from the Pix2Pix architecture to take Cone Penetration Test (CPT) data as a conditional input and generate subsoil schematizations. For training, validation and testing, a database of 24,000 synthetic schematizations of size 32x512...
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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Li, Zirui (author)
End-to-end Automatic Speech Recognition (ASR) systems improved drastically in recent years and they work extremely well on many large datasets. However, research shows that these models failed to capture the variability in speech production and have biases against the variant caused by the regional accented speech. Moreover, ASR research on...
master thesis 2023
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Vlasenko, Mikhail (author)
Inverse Reinforcement Learning (IRL) is a subfield of Reinforcement Learning (RL) that focuses on recovering the reward function using expert demonstrations. In the field of IRL, Adversarial IRL (AIRL) is a promising algorithm that is postulated to recover non-linear rewards in environments with unknown dynamics. This study investigates the...
bachelor thesis 2023
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feng, Clio (author)
Recently, while gaze estimation has gained a substantial improvement by using deep learning models, research had shown that neural networks are weak against adversarial attacks. Despite researchers has been done numerous on adversarial training, there are little to no studies on adversarial training in gaze estimation. Therefore, the objective...
bachelor thesis 2023
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Müller, Lisa-Marie (author)
Across the world, countries are facing housing shortages and the Netherlands is no different. The increasing demand for new housing exceeds the growth rate of the architecture, engineering, and construction industry. Current solutions remain small in scale and therefore unsustainable. Multi-family housing is the optimal typology to address the...
master thesis 2023
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Thomas, Wessel (author)
Network Intrusion Detection Systems (NIDSs) defend our computer networks against malicious network attacks. Anomaly-based NIDSs use machine learning classifiers to categorise incoming traffic. Research has shown that classifiers are vulnerable to adversarial examples, perturbed inputs that lead the classifier into misclassifying the input....
master thesis 2023
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do Lago, Cesar A.F. (author), Giacomoni, Marcio H. (author), Bentivoglio, Roberto (author), Taormina, R. (author), Gomes, Marcus N. (author), Mendiondo, Eduardo M. (author)
Two-dimensional hydrodynamic models are computationally expensive. This drawback can limit their application to solving problems requiring real-time predictions or several simulation runs. Although the literature presented improvements in using Deep Learning as an alternative to hydrodynamic models, Artificial Neural Networks applications for...
journal article 2023
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Bruggink, Daan (author)
Traversability estimation is a key component in autonomous driving tasks. In many applications, semantic segmentation is used to pixel-wise classify a visual scene. The pixel-wise segmented map is used to estimate the traversability of different environments. The semantic segmentation accuracy can drop if environmental conditions change. The...
master thesis 2023
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Afriat, Eliott (author)
We seek to examine the vulnerability of BERT-based fact-checking. We implement a gradient based, adversarial attack strategy, based on Hotflip swapping individual tokens from the input. We use this on a pre-trained ExPred model for fact-checking. We find that gradient based adversarial attacks are ineffective against ExPred. Uncertainties about...
bachelor thesis 2023
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Focante, Edoardo (author)
In recent years, neural networks (NNs) have seen a surge in popularity due to their ability to model complex patterns and relationships in data. One of the challenges of using NNs is the requirement for large amounts of labelled data to train the model effectively. In many real-world applications such as radar, labelled data may be scarce due to...
master thesis 2023
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Aljuffri, A.A.M. (author), Saxena, Mudit (author), Reinbrecht, Cezar (author), Hamdioui, S. (author), Taouil, M. (author)
Security is one of the most important features that a system must provide. Depending on the application of the target device, different threats should be considered at design time. However, the attack space is vast. Hence, it is difficult to decide what components to protect, what level of protection they require and how efficient they are in...
conference paper 2023
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Lupetti, M.L. (author), Cavalcante Siebert, L. (author), Abbink, D.A. (author)
In this paper, we problematize popular narratives of driving automation. Whether positive or negative, these propagate simplistic assumptions about human abilities and reinforce technocratic approaches to mobility innovation. We build on narrative approaches to participatory research and adversarial design, to explore how design-led...
conference paper 2023
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Chen, Yunjie (author), Staring, M. (author), Wolterink, Jelmer M. (author), Tao, Q. (author)
In radiological practice, multi-sequence MRI is routinely acquired to characterize anatomy and tissue. However, due to the heterogeneity of imaging protocols and contraindications to contrast agents, some MRI sequences, e.g. contrast-enhanced T1-weighted image (T1ce), may not be acquired. This creates difficulties for large-scale clinical...
conference paper 2023
Searched for: subject%3A%22adversarial%22
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