Searched for: subject%3A%22Network%22
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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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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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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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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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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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Yang, Wei-Tse (author)
We present the first deep learning approach to estimate the human skeletal system of the musculoskeletal model from monocular video. The current practice of musculoskeletal modeling relies on a motion capture system and OpenSim. The data is recorded in a restricted environment, and OpenSim workflow for musculoskeletal modeling is costly. Our...
master thesis 2021
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Jeken Rico, P. (author)
The following project deals with the optimization of simulation parameters such as the injection location and pitch angle of polyurethane foaming simulations using artificial neural networks. The model's target is to predict quality variables based on the process parameters and the geometry features. Through several evaluations of the model,...
master thesis 2021
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Lanzini, Edoardo (author)
The natural world is long-tailed: rare classes are observed orders of magnitudes less frequently than common ones, leading to highly-imbalanced data where rare classes can have only handfuls of examples. Learning from few examples is a known challenge for deep learning based classification algorithms, and is the focus of the field of low-shot...
bachelor thesis 2021
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Felicia Elfrida Tjhai, Felicia (author)
There is growing research on automated video summarization following the rise of video content. However, the subjectivity of the task itself is still an issue to address. This subjectivity stems from the fact that there can be different summaries for the same video depending on which parts one considers important. Supervised models especially...
bachelor thesis 2021
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Barad, Kuldeep (author)
Autonomous vision-based navigation is a crucial element for space applications involving a potentially uncooperative target, such as proximity operations for on-orbit servicing or active debris removal. Due to low mass and power characteristics, monocular vision sensors are an attractive choice for onboard vision-based navigation systems. This...
master thesis 2020
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El Haji, Khalid (author), Posner, Noah (author), Ilbaş, Hakan (author), Karpuz, Sergen (author), Wernet, Victor (author)
As the population increases so does the waste that is generated. Manually recycling waste is expensive and slow. Computer Vision (CV) solutions aim to make this less expensive and faster. Lots of data of this waste (thousands of images) is needed to train these CV solutions. This project, called Synthetic Waste Generator (SWaG) can create...
bachelor thesis 2020
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Mody, Prerak (author)
The onset of delirium, a disturbance in the mental activities of a patient, can be potentially detected by understanding activities within an Intensive Care Unit (ICU) room. Such activities can be extracted by estimating human pose via a visual capture of the scene. This work uses a top-view depth camera in an ICU room to estimate pose of the...
master thesis 2020
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Lelekas, Ioannis (author)
Biological vision adopts a coarse-to-fine information processing pathway, from initial visual detection and binding of salient features of a visual scene, to the enhanced and preferential processing given relevant stimuli. On the contrary, CNNs employ a fine-to-coarse processing, moving from local, edge-detecting filters to more global ones...
master thesis 2020
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van Dijk, Tom (author)
With a growing number of drones, the risk of collision with other air traffic or fixed obstacles increases. New safety measures are required to keep the operation of Unmanned Aerial Vehicles (UAVs) safe. One of these measures is the use of a Collision Avoidance System (CAS), a system that helps the drone autonomously detect and avoid obstacles....
report 2020
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Wang, Yizhou (author)
In the past few years, convolutional neural networks (CNNs) have been widely utilized and shown state-of-the-art performances on computer vision tasks. However, CNN based approaches usually require a large amount of storage, run-time memory, as well as computation power in both training and inference time, which are usually used on GPU based...
master thesis 2019
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Sun, Wei (author)
This work applies keypoint detection method to solve gate recognition problem. Unlike regular object detection task, gate recognition problem is made difficult by the fact that gate is empty wireframe which means that the object surrounded by gate-edge is not relevant and should not be taken into consideration when detecting. However, regular...
master thesis 2019
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Dürnay, Philipp (author)
Autonomous MAV are an emerging technology that supports a wide range of applications such as medical delivery or finding survivors in disaster scenarios. As flying in such missions is difficult the robust estimation of an MAV's state within its environment is crucial to ensure safe operation. In indoor scenarios, cameras are one of the...
master thesis 2018
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Dhar, Aniket (author)
Convolutional neural networks are showing incredible performance in image classification, segmentation, object detection and other computer vision applications in recent years. But they lack understanding of affine transformations to input data. In this work, we introduce rotational invariant<br/>convolutional neural networks that learn...
master thesis 2018
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Hommos, Omar (author)
Action recognition continues to receive significant attention from the research community, with new neural network architectures being developed continuously. Optical flow is by far the most popular input motion representation to these architectures, leaving a lot of undiscovered potential for other types of motion representations. Eulerian...
master thesis 2018
Searched for: subject%3A%22Network%22
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