Searched for: subject%3A%22CNN%22
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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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Maiorano, Luigi (author)
While image-based georeferencing systems are widely available, none are designed for edge computing on board small satellites in space. Recent advances in autonomous data processing allow points of interest (POIs) to be identified in the captured images, enabling prioritization of data and reducing required downlink bandwidths. Directly...
master thesis 2023
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van den Berg, Jasper (author)
The traumatic loss of a hand is a horrific experience usually followed by significant psychological, functional and rehabilitation challenges. Even though much progress has been made in the past decades, the prosthetic challenge of restoring the human hand functionality is still far from being achieved. Autonomous prosthetic hands showed...
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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Mullaj, Dajt (author)
Deep convolutional neural networks (CNNs) have achieved current state-of-the-art in image denoising, but require large datasets for training. Their performance remains limited on smaller real-noise datasets. In this paper, we investigate robust deep learning denoising using transfer learning. We explore the impact of dataset sizes, CNN parameter...
master thesis 2023
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CHANOPOULOU, IOANNA (author)
Convolutional Neural Networks (CNNs) have emerged primarily from research focusing on image classification tasks and as a result, most of the well-motivated design choices found in literature are relevant to computer vision applications. CNNs' application on Imaging Mass Spectrometry (IMS) data is quite recent and involves new challenges, such...
master thesis 2023
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Smit, Winstijn (author)
Touchless interaction with computers has become more important in recent years, especially in the context of the COVID-19 pandemic.<br/>Applications include situations where touch input is not possible or not desirable, e.g. for hygienic purposes in a public setting or a medical setting.<br/>Practical examples for touchless interaction include...
bachelor thesis 2023
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Therias, Adele (author)
The production of cocoa beans contributes to 7.5% of European Union (EU) driven deforestation. For this reason, the recent European Union Deforestation-free Regulation (EUDR) requires producers to perform comprehensive tracking of cocoa farm extents. However, cocoa crops present unique detection challenges due to their complex canopy structure,...
master thesis 2023
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Viering, T.J. (author)
This dissertation focuses on safety in machine learning. Our adopted safety notion is related to robustness of learning algorithms. Related to this concept, we touch upon three topics: explainability, active learning and learning curves.<br/><br/>Complex models can often achieve better performance compared to simpler ones. Such larger models are...
doctoral thesis 2023
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Pena Pereira, Simon (author)
Transforming the global energy sector from fossil-fuel based to renewable energy sources is key to limiting global warming and efficiently achieving climate neutrality. The decentralized nature of the renewable energy system allows private households to install photovoltaic (PV) systems on their rooftops. In this context, planning an efficient...
master thesis 2023
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Su, Jiahang (author), Li, Shuai (author), Wolff, Lennard (author), van Zwam, Wim (author), Niessen, W.J. (author), van der Lugt, Aad (author), van Walsum, T. (author)
Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and...
journal article 2023
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Chaudhary, Shivam (author), Prasad Miyapuram, Krishna (author), Lomas, J.D. (author)
Entrainment is a phenomenon of phase or temporal matching of one system with that of another system. Human neural activity has been shown to resonate with external auditory stimuli. When we enjoy a piece of music, there is a resonance of brain responses with auditory signals. The crux of music cognition is based on this resonance of musical...
conference paper 2023
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Estebanez Camarena, M. (author), Taormina, R. (author), van de Giesen, N.C. (author), ten Veldhuis, Marie-claire (author)
Food and economic security in West Africa rely heavily on rainfed agriculture and are threatened by climate change and demographic growth. Accurate rainfall information is therefore crucial to tackling these challenges. Particularly, information about the occurrence and length of droughts as well as the onset date of the rainy season is...
journal article 2023
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Ghahremani, A. (author), Lofi, C. (author)
Reliable Cardiovascular Disease (CVD) classification performed by a smart system can assist medical doctors in recognizing heart illnesses in patients more efficiently and effectively. Electrocardiogram (ECG) signals are an important diagnostic tool as they are already available early in the patients’ health diagnosis process and contain...
journal article 2023
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Estebanez Camarena, M. (author), Curzi, Fabio (author), Taormina, R. (author), van de Giesen, N.C. (author), ten Veldhuis, Marie-claire (author)
West African food systems and rural socio-economics are based on rainfed agriculture, which makes society highly vulnerable to rainfall uncertainty and frequent floods and droughts. Reliable rainfall information is currently missing. There is a sparse and uneven rain gauge distribution and, despite continuous efforts, rainfall satellite products...
journal article 2023
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Ji, M. (author), Al-Ars, Z. (author), Hofstee, H.P. (author), Chang, Yuchun (author), Zhang, Baolin (author)
Convolutional neural networks (CNNs) are to be effective in many application domains, especially in the computer vision area. In order to achieve lower latency CNN processing, and reduce power consumption, developers are experimenting with using FPGAs to accelerate CNN processing in several applications. Current FPGA CNN accelerators usually use...
journal article 2023
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Guendel, Ronny (author), Ullmann, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Radar-based human activity recognition in crowded environments using regression approaches is addressed. Whereas previous research has focused on single activities and subjects, the problem of continuous activity recognition involving up to five individuals moving in arbitrary directions in an indoor area is introduced. To treat the problem, a...
conference paper 2023
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Presekal, A. (author), Stefanov, Alexandru (author), Subramaniam Rajkumar, Vetrivel (author), Palensky, P. (author)
The cyber attacks in Ukraine in 2015 and 2016 demonstrated the vulnerability of electrical power grids to cyber threats. They highlighted the significance of Operational Technology (OT) communication-based anomaly detection. Many anomaly detection methods are based on real-time traffic monitoring, i.e., Intrusion Detection Systems (IDS) that may...
conference paper 2023
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Liu, Huan (author), Wang, Shilei (author), Jing, Guoqing (author), Yu, Ziye (author), Yang, Jin (author), Zhang, Yong (author), Guo, Y. (author)
Vehicle-mounted ground-penetrating radar (GPR) has been used to non-destructively inspect and evaluate railway subgrade conditions. However, existing GPR data processing and interpretation methods mostly rely on time-consuming manual interpretation, and limited studies have applied machine learning methods. GPR data are complex, high...
journal article 2023
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Zheng, Feifei (author), Yin, Hang (author), Ma, Yiyi (author), Duan, Huan Feng (author), Gupta, Hoshin (author), Savic, Dragan (author), Kapelan, Z. (author)
Under global climate change, urban flooding occurs frequently, leading to huge economic losses and human casualties. Extreme rainfall is one of the direct and key causes of urban flooding, and accurate rainfall estimates at high spatiotemporal resolution are of great significance for real-time urban flood forecasting. Using existing rainfall...
journal article 2023
Searched for: subject%3A%22CNN%22
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