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Kam, Berend (author)<br/>Machine learning algorithms (learners) are typically expected to produce monotone learning curves, meaning that their performance improves as the size of the training dataset increases. However, it is important to note that this behavior is not universally observed. Recently monotonicity of learning curves has gained renewed attention, as...master thesis 2023
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Gielisse, A.S. (author)Most recent works on optical flow use convex upsampling as the last step to obtain high-resolution flow. In this work, we show and discuss several issues and limitations of this currently widely adopted convex upsampling approach. We propose a series of changes, inspired by the observation that convex upsampling as currently implemented performs...master thesis 2023
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Gökçe, Tolga (author)An algal bloom is defined as a rapid increase in common algae (phytoplankton) abundance in water bodies and it can occur when a group of certain environmental factors is combined. If the algae populations grow out of control, such algal blooms become problematic and cause damage to the ecosystem, such phenomena are called harmful algal blooms....bachelor thesis 2023
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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
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Alvarez Lucendo, Rodrigo (author)Forecasting algal blooms using remote sensing data is less labour-intensive and has better cover- age in time and space than direct water sampling. The paper implements a deep learning technique, the UNet Architecture, to predict the chlorophyll concentration, which is a good indicator for al- gal bloom in the Rio Negro water reservoirs of...bachelor thesis 2023
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Lubbers, Rob (author)The aim of this paper is to find out which Machine Learning (ML) model predicts the concentration of Chlorophyll-a, in the Palmar lake in Uruguay best. Currently there are no such models to predict the growth in this lake. The algorithms which will be compared in this paper are a Linear Regression model and the U-Net model. We will compare the...bachelor thesis 2023
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de Gruyl, Einar (author)This research presents a method for forecasting algal blooms using remote sensing with spatially and temporally sparse satellite data. The method involves the use of multiple interpolation methods to interpolate the sparse input data. The approach is shown to be effective in predicting algal blooms in areas where data is sparse, and the results...bachelor thesis 2023
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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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Quist, Joris (author)Binary Neural Networks (BNNs) are compact and efficient by using binary weights instead of real-valued weights. Current BNNs use latent real-valued weights during training, where several training hyper-parameters are inherited from real-valued networks. The interpretation of several of these hyperparameters is based on the magnitude of the real...master thesis 2022
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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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Chandran, Godwin Rayan (author)Video Object Detectors (VID) are used in various applications such as surveillance, inspection, etc. Often in these applications there exists a spatial area of interest and a static background. The static backgrounds remain constant throughout the video sequence in the training data establishing an undesirable correlation with the moving object...master thesis 2022
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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
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Feng, Chengming (author)Deep learning has been widely implemented in industrial inspection, such as damage detection from images. However, training deep networks requires massive data, which is hard to collect and laborious to annotate, especially in the aviation scenario of aircraft engines. To alleviate the demand for annotated data, we create BladeSynth - a large...master thesis 2022
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Bao, Ziyu (author)Regression is difficult because of noise, imbalanced data sampling, missing data, etc. We propose a method by classifying the continuous regression labels to tackle regression robustness problems. We analyze if our method can help regression, given that the class information is already included in the regression labels. We start by extensively...master 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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Zhang, Xiangxie (author)Location information is essential for the ViT model. Image data has three types of location information: absolute location, relative direction, and relative distance. Various position embeddings methods have been used to introduce location information to the ViT model. Some existing methods are absolute position embeddings, relative position...master thesis 2022
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Kok, Jim (author)COVID-19 drastically raised the importance of non-contact based healthcare methods. Low blood oxygen levels of a person, which can be unnoticeable, are potentially a precursor of COVID-19. Contact based methods for measuring blood oxygen saturation could spread the contagious disease. Therefore, this paper investigates non-contact RGB camera...master thesis 2022
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Zeng, Liang (author)Self-supervised contrastive learning has achieved remarkable performance in computer vision. Its success relies on certain priors that vary from different tasks and data at hand, e.g, the object-centric prior implied by ImageNet. For segmentation on complex scenes, researchers have introduced salient objects or auxiliary labels as priors to...master thesis 2022
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Voorhout, Damian (author)Traditional convolutional neural networks exhibit an inherent limitation, they can not adapt their computation to the input while some inputs require less computation to arrive at an accurate prediction than others. Early-exiting setups exploit this fact by only spending as much computation as is necessary and subsequently exiting the sample...master thesis 2022
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Streefkerk, Thomas (author)CycleGANs [1] and CIConv [2] are both relatively new approaches to their respective applications. For CycleGANs this application is unpaired image-to-image domain adaptation and for CIConv this application is making images more<br/>robust to illumination changes. We investigate whether CycleGANs in combination with CIConv can be used to improve...bachelor thesis 2022