Searched for: subject%3A%22Convolutional%255C%2BNeural%255C%2BNetwork%22
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Edixhoven, Tom (author)
In this work we show how Group Equivariant Convolutional Neural Networks use subsampling to learn to break equivariance to their symmetries. We focus on the 2D roto-translation group and investigate the impact of broken equivariance on network performance. We show that changing the input dimension of a network by as little as a single pixel can...
master thesis 2023
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Jiang, Longxing (author)
Convolutional Neural Networks (CNN) have become a popular solution for computer vision problems. However, due to the high data volumes and intensive computation involved in CNNs, deploying CNNs on low-power hardware systems is still challenging.<br/>The power consumption of CNNs can be prohibitive in the most common implementation platforms:...
master thesis 2022
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Pasqualetto Cassinis, L. (author)
Activities in outer space have entered a new era of growth, fostering human development and improving key Earth-based applications such as remote sensing, navigation, and telecommunication. The recent creation of SpaceX's Starlink constellation as well as the steep increase in CubeSat launches are expected to revolutionize the way we use space...
doctoral 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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Lipman, Lars (author)
<b>Introduction </b>- Grasping unknown objects is an important ability for robots in logistic environments. While humans have an excellent understanding of how to grasp objects because of their visual perception and understanding of the 3D world, robotic grasping is still a challenge. Due to the fast-growing development of deep learning methods,...
master thesis 2022
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van Hemert, Guus (author)
To study the aerosols in the atmosphere is an important aspect for getting a better understanding of climate change. Therefore, it is important to get accurate observations of aerosols in the atmosphere as well as accurate emission fluxes of aerosol species. Satellite instruments such as SPEXone are able to measure aerosol properties with a high...
master thesis 2022
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Blankendal, Philip (author)
Side-channel attacks leverage the unintentional leakage of information that indirectly relates to cryptographic secrets such as encryption keys. Previous settings would involve an attacker conducting some manual-statistical analysis to exploit this data and retrieve sensitive information from the target. With the adoption of deep learning...
master thesis 2022
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Claassen, Carlijn (author)
The combination of the high number and the consequences of falls in older adults led to the development of fall risk assessments; non-sensor-based and sensor-based. Multiple studies used ML for older adults' fall risk prediction using raw IMU data. This study's objective was to develop a DL algorithm that predicts the fall risk of people living...
master thesis 2022
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Narchi, William (author)
This paper presents how a convolutional neural network can be constructed in order to recognise gestures using photodiodes and ambient light. A number of candidates are presented and evaluated, with the most performant being adopted for in-depth analysis. This network is then compressed in order to be ran on an Arduino Nano 33 BLE...
bachelor thesis 2022
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Tahur, Nishad (author)
Color information has been shown to provide useful information during image classification. Yet current popular deep convolutional neural networks use 2-dimensional convolutional layers. The first 2-dimensional convolutional layer in the network combines the color channels of the input images, which produces feature maps per channel with only...
master thesis 2022
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Chen, Qilin (author)
Convolutional neural networks (CNNs) are often pruned to achieve faster training and inference speed while also requiring less memory. Nevertheless, during computation, most modern GPUs cannot take advantage of the sparsity automatically, especially on networks with unstructured sparsity. Therefore, many libraries that exploit sparsity, have...
bachelor thesis 2022
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Quin, Tristan (author)
This research investigates the efficacy and reliability of geometric matching for the specific case of aligning non-exact copies of artistic works with the original from which they were derived. The purpose of which is to provide a foundation for comparison in any further analysis conducted by conservators and art historians. An overview of the...
bachelor thesis 2022
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Buitenweg, Jurriaan (author)
To reduce food waste, the strawberry harvesting process should be optimized. In the modern era, computer vision can provide huge amounts of help. This paper focuses on optimizing pre-trained convolutional neural networks (CNN) to determine the maturity level of strawberries on a 1-10 scale. Here, 1 means unripe and 10 means overripe. Maturity...
bachelor thesis 2022
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Bechtold, Jeroen (author)
This paper tries to combat the food waste of strawberries during the harvesting steps.<br/>An automatic pipeline must be established to combat this food waste.<br/>One of the steps needed in this pipeline is detecting strawberries in images.<br/>Therefore, this paper aims to find out which Convolutional Neural Network (CNN) can be best used to...
bachelor thesis 2022
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Louwen, Anton (author)
Radio frequency fingerprinting has been identified as a method to increase integrity in aircraft surveillance while retaining its openness. One way to uniquely determine transmitting devices is to distill the device its radio frequency (RF) fingerprint by looking at the physical features of the message signal it transmits. This physical layer...
master thesis 2022
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Bos, Roel (author)
Unmanned Ground Vehicle (UGV) navigation in unstructured off-road environments can benefit from accurate traversability estimation. Often, experiments with UGVs use semantic segmentation networks for visual scene understanding. Based on the pixel-wise classification of a semantic segmentation network, the UGV can distinguish traversable from non...
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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Verschoor, Fleur (author)
Satellite data, such as optical and Synthetic Aperture Radar imagery, can provide information about the location and level of destruction caused by natural hazards. This information is essential to optimise the rescue mission logistics by humanitarian aid organisations and save people in need. Currently, many Automatic Damage Assessment (ADA)...
master thesis 2022
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Norder, Lucas (author)
Conventional Topology Optimization (TO) enables the inverse design of nanophotonic structures by specifying the objective and constraints without a predefined topological concept. Yet, extreme scenarios such as the design of a...
master thesis 2022
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Eijgenraam, Bram (author)
How to deal with the presence of weather affected data is an unavoidable topic in the processing of optical imagery. Clouds and cloud shadows significantly alter the spectral signatures obtained from satellite data, which often leads to problems for any kind of scientific analysis. In this research there has been elaborated on two different kind...
master thesis 2022
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