Essays about: "multimodal modell"

Showing result 1 - 5 of 14 essays containing the words multimodal modell.

  1. 1. Branching Out with Mixtures: Phylogenetic Inference That’s Not Afraid of a Little Uncertainty

    University essay from KTH/Matematisk statistik

    Author : Ricky Molén; [2023]
    Keywords : Phylogeny; Bayesian analysis; Markov chain Monte Carlo; Variational inference; Mixture of proposal distributions; Fylogeni; Bayesiansk analys; Markov Chain Monte Carlo; Variationsinferens; Mixturer av förslagsfördelningar;

    Abstract : Phylogeny, the study of evolutionary relationships among species and other taxa, plays a crucial role in understanding the history of life. Bayesian analysis using Markov chain Monte Carlo (MCMC) is a widely used approach for inferring phylogenetic trees, but it suffers from slow convergence in higher dimensions and is slow to converge. READ MORE

  3. 2. Deep Learning-Driven EEG Classification in Human-Robot Collaboration

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

    Author : Yuan Wo; [2023]
    Keywords : Human-robot collaboration; Electroencephalogram signal; Signal Processing Feature Extraction; Deep Learning method; Dilated Convolutional Neural Network; Människa-robot-samarbete; Elektroencefalogram-signal; Signalförädlingsfunktionsutvinning; Djupinlärningsmetod; Dilaterat konvolutionellt neuronnätverk.;

    Abstract : Human-robot collaboration (HRC) occurs when people and robots work together in a shared environment. Current robots often use rigid programs unsuitable for HRC. Multimodal robot programming offers an easier way to control robots using inputs like voice and gestures. READ MORE

  4. 3. A real-time Multi-modal fusion model for visible and infrared images : A light-weight and real-time CNN-based fusion model for visible and infrared images in surveillance

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

    Author : Jin Wanqi; [2023]
    Keywords : Image fusion; deep learning; surveillance; CNN; real time; Bildfusion; djupinlärning; övervakning; CNN; realtid;

    Abstract : Infrared images could highlight the semantic areas like pedestrians and be robust to luminance changes, while visible images provide abundant background details and good visual effects. Multi-modal image fusion for surveillance application aims to generate an informative fused images from two source images real-time, so as to facilitate surveillance observatory or object detection tasks. READ MORE

  5. 4. Text-Driven Fashion Image Manipulation with GANs : A case study in full-body human image manipulation in fashion

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

    Author : Reza Dadfar; [2023]
    Keywords : Multimodal fashion image editing; Generative adversarial network inversion; Text-driven image manipulation; TD-GEM; Multimodal modebildredigering; Generativa adverserial Nätverk inversion; Text-driven bildmanipulation; TD-GEM;

    Abstract : Language-based fashion image editing has promising applications in design, sustainability, and art. However, it is considered a challenging problem in computer vision and graphics. The diversity of human poses and the complexity of clothing shapes and textures make the editing problem difficult. READ MORE

  6. 5. Multi-modal Models for Product Similarity : Comparative evaluation of unimodal and multi-modal architectures for product similarity prediction and product retrieval

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

    Author : Christos Frantzolas; [2023]
    Keywords : Computer Vision; Natural Language Processing; Representation Learning; Metric Learning; Multimodal Retrieval; Bildigenkänning; Språkteknologi; Representationsinlärning; Metrisk inlärning; Multimodal informationssökning;

    Abstract : With the rapid growth of e-commerce, enabling effective product recommendation systems and improving product search for shoppers plays a crucial role in driving customer satisfaction. Traditional product retrieval approaches have mainly relied on unimodal models focusing on text data. READ MORE