Sökning: "Convolutional"

Visar resultat 1 - 5 av 304 uppsatser innehållade ordet Convolutional.

  1. 1. Malignant Melanoma Classification with Deep Learning

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Jakob Kisselgof; [2019]
    Nyckelord :Melanoma classification deep learning;

    Sammanfattning : Malignant melanoma is the deadliest form of skin cancer. If correctly diagnosed in time, the expected five-year survival rate can increase up to 97 %. Therefore, exploring various methods for early detection can contribute with tools which can be used to improve detection of disease and finally to make sure that help is given in time. LÄS MER

  2. 2. Object Detection in Object Tracking System for Mobile Robot Application

    Master-uppsats, KTH/Matematisk statistik

    Författare :Alessandro Foa'; [2019]
    Nyckelord :;

    Sammanfattning : This thesis work takes place at the Emerging Technologies department of Volvo Construction Equipment(CE), in the context of a larger project which involves several students. The focus is a mobile robot built by Volvo for testing some AI features such as Decision Making, Natural Language Processing, Speech Recognition, Object Detection. LÄS MER

  3. 3. A Comparative Study of Facial Recognition Techniques : With focus on low computational power

    Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi; Högskolan i Skövde/Institutionen för informationsteknologi; Högskolan i Skövde/Institutionen för informationsteknologi

    Författare :Timmy Schenkel; Oliver Ringhage; Nicklas Branding; [2019]
    Nyckelord :Machine Learning; Facial Recognition; Low Computational Power;

    Sammanfattning : Facial recognition is an increasingly popular security measure in scenarios with low computational power, such as phones and Raspberry Pi’s. There are many facial recognition techniques available. The aim is to compare three such techniques in both performance and time metrics. LÄS MER

  4. 4. Video Saliency Detection using Deep Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jakob Wiesinger; [2019]
    Nyckelord :;

    Sammanfattning : A deep learning model for video saliency detection is proposed and trained. The neural network architecture combines recent innovations in the field: A twostream approach merges two separate input streams for appearance and motion aspects of saliency. Pre-trained convolutional features detect objectness. LÄS MER

  5. 5. Region Proposal Based Object Detectors Integrated With an Extended Kalman Filter for a Robust Detect-Tracking Algorithm

    Master-uppsats, Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)

    Författare :Gabriel Khajo; [2019]
    Nyckelord :Object Detection; Extended Kalman Filter; Tracking;

    Sammanfattning : In this thesis we present a detect-tracking algorithm (see figure 3.1) that combines the detection robustness of static region proposal based object detectors, like the faster region convolutional neural network (R-CNN) and the region-based fully convolutional networks (R-FCN) model, with the tracking prediction strength of extended Kalman filters, by using, what we have called, a translating and non-rigid user input region of interest (RoI-) mapping. LÄS MER