Essays about: "network partitioning"

Showing result 1 - 5 of 34 essays containing the words network partitioning.

  1. 1. Scalable Nonparametric L1 Density Estimation via Sparse Subtree Partitioning

    University essay from Uppsala universitet/Statistik, AI och data science

    Author : Axel Sandstedt; [2023]
    Keywords : density estimation; scalable density estimation; nonparametric density estimation; scalable nonparametric density estimation; L1; L_1; anomaly detection; regression analysis;

    Abstract : We consider the construction of multivariate histogram estimators for any density f seeking to minimize its L1 distance to the true underlying density using arbitrarily large sample sizes. Theory for such estimators exist and the early stages of distributed implementations are available. READ MORE

  3. 2. A comparison of neuron touch detection algorithms utilising voxelization and the data structures octree, k-d tree and R-tree

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Jonathan Gustaf Cilli; Karin De Verdier; [2023]
    Keywords : ;

    Abstract : Simulations of biologically detailed neuronal networks have become an essential tool in the study of the brain. An important step in the creation of these types of simulations is the detection of the connections between the nerve cells. This paper analyses the efficiency of four algorithms used for such purposes. READ MORE

  4. 3. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Ziyou Li; [2023]
    Keywords : Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Abstract : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. READ MORE

  5. 4. Reducing the computational complexity of a CNN-based neural network used for partitioning in VVC compliant encoders

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Saman Rassam; [2022]
    Keywords : Video Coding; VVC; Block Partitioning; VTM; ANN; CNN; Videkodning; VVC; Blockpartitionering; VTM; ANN; CNN;

    Abstract : Block partitioning is a computationally heavy step in the video coding process. Previously, this stage has been done using a full-search-esque algorithm. READ MORE

  6. 5. Simulations of Point Processes on Directed Graphs

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Stavroula Rafailia Vlachou; [2022]
    Keywords : ;

    Abstract : Simulating a point process where the events correspond to vehicle collisions on a road networkcan be quite computationally heavy due to the large number of elements that are necessary toprovide a sufficient discretization of the network. This paper aims to present a computationallyefficient solution for simulating events of a point process. READ MORE