Searched for: subject%3A%22Self%255C-supervised%255C+learning%22
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Rijpkema, Gerben (author)
Forensic microtrace investigation relies on a time- and labour-intensive process of manually analysing samples via microscopy. To aid forensic experts in their investigations, an image recognition model for microtrace localisation and classification is needed. This work investigates the trace recognition accuracy that can be achieved by...
master thesis 2024
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Sebus, Siert (author)
The Deep Neural Network (DNN) has become a widely popular machine learning architecture thanks to its ability to learn complex behaviors from data. Standard learning strategies for DNNs however rely on the availability of large, labeled datasets. Self-Supervised Learning (SSL) is a style of learning that allows models to also use unlabeled data...
master thesis 2024
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Dong, Y. (author), Lu, Xingmin (author), Li, Ruohan (author), Song, Wei (author), van Arem, B. (author), Farah, H. (author)
The burgeoning navigation services using digital maps provide great convenience to drivers. However, there are sometimes anomalies in the lane rendering map images, which might mislead human drivers and result in unsafe driving. To accurately and effectively detect the anomalies, this paper transforms lane rendering image anomaly detection into...
poster 2024
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Paredes-Vallés, Federico (author)
In the ever-evolving landscape of robotics, the quest for advanced synthetic machines that seamlessly integrate with human lives and society becomes increasingly paramount. At the heart of this pursuit lies the intrinsic need for these machines to perceive, understand, and navigate their surroundings autonomously. Among the senses, vision...
doctoral thesis 2023
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Liu, Kevin (author)
This master’s thesis explores the application of Self-Supervised Contrastive Learning (SSCL), specifically the SimCLR algorithm, to enhance feature representation learning from Wafer Bin Maps (WBM) in the semiconductor manufacturing process. The motivation stems from the industry’s growing need for automated defect detection and root-cause...
master thesis 2023
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Xu, Y. (author)
Micro air vehicles (MAVs) have shown significant potential in modern society. The development in robotics and automation is changing the roles of MAVs from remotely controlled machines requiring human pilots to autonomous and intelligent robots. There is an increasing number of autonomous MAVs involved in outdoor operations. In contrast, the...
doctoral thesis 2023
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Poulakakis Daktylidis, Stelios (author)
There exists a fundamental gap between human and artificial intelligence. Deep learning models are exceedingly data hungry for learning even the simplest of tasks, whereas humans can easily adapt to new tasks with just a handful of samples. Unsupervised few-shot learning (U-FSL) aspires to bridge this gap, without relying on costly annotations....
master thesis 2023
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Farah, Youssef (author)
Event cameras are novel bio-inspired sensors that capture motion dynamics with much higher temporal resolution than traditional cameras, since pixels react asynchronously to brightness changes. They are therefore better suited for tasks involving motion such as motion segmentation. However, training event-based networks still represents a...
master thesis 2023
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Dijkstra, Jonathan (author)
In recent years, the agricultural sector has seen significant techno- logical improvements under the flag of precision agriculture, assisting farmers in the manageability that coincides with large-scale farming. Moreover, precision agriculture aims to enable plant-specific farming on the macro scale that is demanded by the current global...
master thesis 2023
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den Ridder, Luc (author)
Although deep reinforcement learning (DRL) is a highly promising approach to learning robotic vision-based control, it is plagued by long training times. This report introduces a DRL setup that relies on self-supervised learning for extracting depth information valuable for navigation. Specifically, a literature study is conducted to investigate...
master thesis 2023
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Spengler, Daniel (author)
The study of tumor microenvironments (TMEs) and immune cell composition in cancer, a disease characterized by uncontrolled growth and spread of tumor cells, has become increasingly important for understanding tumor progression and patient outcomes. Tools such as the TME-Analyzer enable this kind of research, but their manual workflows highlight...
master thesis 2023
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Cui, Jianfeng (author)
We explored the possibility of improving cross-view matching performance with self-supervised learning techniques and perform interpretations in terms of the embedding space of image features. The effect of pre-training by contrastive learning is verified quantitatively by experiments, and also exhibited by visualization of the feature space.
master thesis 2023
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Naseri Jahfari, A. (author), Tax, D.M.J. (author), van der Harst, Pim (author), Reinders, M.J.T. (author), van der Bilt, Ivo (author)
Background: Smartwatches enable continuous and noninvasive time series monitoring of cardiovascular biomarkers like heart rate (from photoplethysmograms), step counter, skin temperature, et cetera; as such, they have promise in assisting in early detection and prevention of cardiovascular disease. Although these biomarkers may not be directly...
journal article 2023
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Ghorbani, R. (author), Reinders, M.J.T. (author), Tax, D.M.J. (author)
With the progress of sensor technology in wearables, the collection and analysis of PPG signals are gaining more interest. Using Machine Learning, the cardiac rhythm corresponding to PPG signals can be used to predict different tasks such as activity recognition, sleep stage detection, or more general health status. However, supervised...
conference paper 2023
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Duan, Di (author), Yang, Huanqi (author), Lan, G. (author), Li, Tianxing (author), Jia, Xiaohua (author), Xu, Weitao (author)
This paper presents EMGSense, a low-effort self-supervised domain adaptation framework for sensing applications based on Electromyography (EMG). EMGSense addresses one of the fundamental challenges in EMG cross-user sensing—the significant performance degradation caused by time-varying biological heterogeneity—in a low-effort (data-efficient and...
conference paper 2023
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Liu, C. (author), Xu, Y. (author), van Kampen, E. (author), de Croon, G.C.H.E. (author)
In this paper, we propose an obstacle avoidance solution for a 34-gram quadcopter equipped with a monocular camera. The perception of obstacles is tackled by a lightweight convolutional neural network predicting a dense depth map from a captured grey-scale image. The depth network performs self-supervised learning and thus requires no ground...
journal article 2023
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Fu, Yuan (author)
Facial expression recognition on head-mounted devices (HMDs) is an intriguing research field because of its potential in various applications, such as interactive virtual reality video meetings. Existing work focuses on building a supervised learning pipeline that utilizes a vast amount of labeled periocular images taken by the built-in cameras....
master thesis 2022
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Shirekar, Ojas (author)
A primary trait of humans is the ability to learn rich representations and relationships between entities from just a handful of examples without much guidance. Unsupervised few-shot learning is an undertaking aimed at reducing this fundamental gap between smart human adaptability and machines. We present a contrastive learning scheme for...
master thesis 2022
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Brouwer, Hans (author)
Synthesizing audio-reactive videos to accompany music is challenging multi-domain task that requires both a visual synthesis skill-set and an understanding of musical information extraction. In recent years a new flexible class of visual synthesis methods has gained popularity: generative adversarial networks. These deep neural networks can be...
master thesis 2022
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Ji, Hang (author)
In this thesis, we analyzed and compared speech representations extracted from different frozen self-supervised learning (SSL) speech pre-trained models on their ability to capture articulatory feature (AF) information and their subsequent prediction of phone recognition performance in within-language and cross-language scenarios. Specifically,...
master thesis 2022
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