Essays about: "Convolution Kernels"

Found 3 essays containing the words Convolution Kernels.

  1. 1. Effects of visualization using different convolution kernels in Julia

    University essay from KTH/Skolan för teknikvetenskap (SCI)

    Author : Nils Forsberg; Axel Nilsson; [2023]
    Keywords : Convolution; Julia; visualization; streamlines; vorticity; interpolation; filter;

    Abstract : Many real-world engineering problems require large amounts of data in order to accurately model and predict outcomes. However, this data is often noisy, sampled and discontinuous, making the data difficult to process and giving rise to incorrect models. READ MORE

  3. 2. Designing Effective Derivative Line Filters: Utilizing convolution to extract extra information

    University essay from KTH/Matematik (Avd.)

    Author : Gustaf Lorentzon; [2023]
    Keywords : Computational Fluid Dynamics; Convolution Filters; Convolution Kernels; Derivatives; Extracting Extra Accuracy; Filtration; Post-processing; Smoothness-Increasing Accuracy-Conserving; Signal-processing; Visualization; Vorticity; Beräkningsbaserad Strömningsdynamik; Faltningsfilter; Faltningskärnor; Derivator; Extrahering av Extra Noggrannhet; Filtrering; Efterbehandling; Kontinuitetsökande; Noggrannhetsbevarande; Signalbehandling; Visualisering; Vorticitet;

    Abstract : The ability to generate accurate approximations of derivatives holds significant importance in numerous scientific fields, including chemistry, economics and fluid mechanics. This thesis is centred around extracting hidden information in data using Smoothness-Increasing Accuracy-Conserving (SIAC) filters. READ MORE

  4. 3. Semantic Segmentation : Using Convolutional Neural Networks and Sparse dictionaries

    University essay from Linköpings universitet/Datorseende

    Author : Viktor Andersson; [2017]
    Keywords : convolution neural network; sparse dictionaries; cnn; computer vision; machine learning; road scene; artificial intelligence; neuronnät; maskininlärning; datorseende; aetificiell intelligens; cnn;

    Abstract : The two main bottlenecks using deep neural networks are data dependency and training time. This thesis proposes a novel method for weight initialization of the convolutional layers in a convolutional neural network. This thesis introduces the usage of sparse dictionaries. READ MORE