Searched for: subject%3A%22convolution%22
(1 - 20 of 216)

Pages

document
Bayraktar, Kerem (author)
The term ”Algal Bloom” refers to the accumulation of algae in a confined geological space. They may harm human health and negatively affect ecological systems around the area. Thus, forecasting algal blooms could mitigate the environmental and socio-economical damages. Particularly, the use of deep learning methods could distinguish underlying...
bachelor thesis 2023
document
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
document
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
document
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
document
Tan, Yicong (author)
Literature on medical imaging segmentation claims that self-attention-based Transformer blocks perform better than convolution in UNet-based architectures. This recently touted success of Transformers warrants an investigation into which of its components contribute to its performance. Moreover, previous work has a limitation of analysis only at...
master thesis 2022
document
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
document
Gajadhar, Vivek (author)
Dose calculations in proton therapy need to be computed as fast as possible for successful cancer treatment planning and execution. The dose calculation algorithms that provide enough accuracy for treatment planning, takes too much time to utilise; therefore there is a need for faster alternatives. One of the alternatives is using a...
bachelor thesis 2022
document
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
document
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
document
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
document
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
document
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
document
Kitsios, Christos (author)
In this thesis, we use a variation of a commutator technique to prove that l^p-stability is independent of p, for p greater than or equal to one, and for convolution-dominated matrices indexed by relatively separated sets in groups of polynomial growth. Moreover, from the inverse-closedness of the Schur matrices we deduce a Wiener type Lemma for...
master thesis 2022
document
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
document
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
document
Bruijns, Ron (author)
Fluvial flooding poses a major threat to mankind and annually leads to major economic losses with many casualties worldwide. The consequences of this can be mitigated when accurate and rapid predictions are available when the water will arrive at which location. Current numerical simulations take a significant amount of time due to their...
master thesis 2022
document
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
document
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
document
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
document
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
Searched for: subject%3A%22convolution%22
(1 - 20 of 216)

Pages