Searched for: subject%253A%2522vision%2522
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Basting, Mark (author)
In real-life scenarios, there are many variations in sizes of objects of the same category and the objects are not always placed at a fixed distance from the camera. This results in objects taking up an arbitrary size of pixels in the image. Vanilla CNNs are by design only translation equivariant and thus have to learn separate filters for...
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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van den Bent, Luuk (author)
master thesis 2023
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Haarman, Luuk (author)
Convolutional Neural Networks (CNNs) benefit from fine-grained details in high-resolution images, but these images are not always easily available as data collection can be expensive or time-consuming. Transfer learning pre-trains models on data from a related domain before fine-tuning on the main domain, and is a common strategy to deal with...
master thesis 2023
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Polak, Max (author)
Incipient slip detection plays an important role in human and robotic grasping. With the growing use of deep learning in vision-based tactile sensing, the black-box nature of these deep neural networks (DNNs) makes it difficult to analyze, debug, and validate their behavior and learned patterns. To fill this gap, eXplainable AI (XAI) methods...
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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Lin, Zhi-Yi (author)
Human 3D kinematics estimation involves measuring joint angles and body segment scales to quantify and analyze the mechanics of human movements. It has applications in areas such as injury prevention, disease identification, and sports science. Conventional marker-based motion capture methods are expensive both in terms of financial investment...
master thesis 2023
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de Boer, Frans (author)
In this paper, we investigate the behaviour of current progress prediction methods on the currently used benchmark datasets. We show that the progress prediction methods can fail to extract useful information from visual data on these datasets. Moreover, when the methods fail to extract visual information, memory-based methods adopt a frame...
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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Oprescu, Teodor (author)
This paper presents an analysis of the data and compute efficiency of the TemporalMaxer deep learning model in the context of temporal action localization (TAL), which involves accurately detecting the start and end times of specific video actions. The study explores the performance and scalability of the TemporalMaxer model under limited...
bachelor thesis 2023
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Sassoon, Jordan (author)
Contrastive Language-Image Pretraining (CLIP) has gained vast interest due to its impressive performance on a variety of computer vision tasks: image classification, image retrieval, action recognition, feature extraction, and more. The model learns to associate images with their descriptions, a powerful method which allows it to perform well on...
bachelor thesis 2023
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Jol, Cees (author)
Strawberries have a short shelf-life time and thus need to be harvested at the right time to reduce waste. To this end, information about quality attributes is useful. Recently, many computer vision methods have been proposed. Most literature analyzes postharvest, which means that strawberries can only be analyzed after harvesting. As a result,...
master thesis 2022
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Sitaldin, Dewwret (author)
In the open world, machine learning (ML) models can encounter a multitude of unknown or novel classes. In a surveillance, safety, or security use case, unknown samples can pose potential threats that are hard to detect since those samples have never been trained on. At the same time, most of the unknowns that will be encountered by a...
master thesis 2022
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POLYA RAMESH, CHINMAY (author)
Camera-based patient monitoring is undergoing rapid adoption in the healthcare sector with the recent COVID-19 pandemic acting as a catalyst. It offers round-the-clock monitoring of patients in clinical units (e.g. ICUs, ORs), or at their homes through installed cameras, enabling timely, pre-emptive care. These are powered by Computer Vision...
master thesis 2022
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Maskam, Richie (author)
Various tasks in the construction industry are tedious due to the high amount of repetition or time-consuming nature. In recent years Deep Learning within computer vision has made it possible to automate various tasks using images. The Hoofdvaarweg Lemmer-Delfzijl has been assessed using images and a pointcloud. The images were being worked with...
master thesis 2022
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Reinhard, Marko (author)
To meet global market demands, it will remain important to further scale up photovoltaics (PV) production. During the production of solar cells, several defects can occur. Current approaches in quality inspection are reaching their speed limits. This thesis project evaluates the feasibility of faster quality inspection by using deep learning...
master thesis 2022
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de Rijk, Philip (author)
Knowledge Distillation (KD) is a well-known training paradigm in deep neural networks where knowledge acquired by a large teacher model is transferred to a small student. KD has proven to be an effective technique to significantly improve the student's performance for various tasks including object detection. As such, KD techniques mostly rely...
master thesis 2022
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Lin, Y. (author)
The humanly constructed world is well-organized in space. A prominent feature of this artificial world is the presence of repetitive structures and coherent patterns, such as lines, junctions, wireframes of a building, and footprints of a city. These structures and patterns facilitate visual scene understanding by providing abundant geometry...
doctoral thesis 2022
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van der Heijden, Lars (author)
Missions to small bodies are increasingly gaining interest as they might hold the secrets to our solar system’s origin while some are also posing a threat to life on Earth. The small size and irregular shape result in complex dynamics complicating the close-proximity operations. Furthermore, due to the long round-trip time communication delays...
master thesis 2022
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Chebykin, Alexander (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
To achieve excellent performance with modern neural networks, having the right network architecture is important. Neural Architecture Search (NAS) concerns the automatic discovery of task-specific network architectures. Modern NAS approaches leverage super-networks whose subnetworks encode candidate neural network architectures. These...
conference paper 2022
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