Sökning: "Classification problem"

Visar resultat 1 - 5 av 585 uppsatser innehållade orden Classification problem.

  1. 1. Convolutional neural networks for semantic segmentation of FIB-SEM volumetric image data

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Fredrik Skärberg; [2020-11-26]
    Nyckelord :Deep learning; convolutional neural networks; image analysis; semantic segmentation; focused ion beam scanning electron microscopy; porous materials; controlled drug release;

    Sammanfattning : Focused ion beam scanning electron microscopy (FIB-SEM) is a well-established microscopytechnique for 3D imaging of porous materials. We investigate three poroussamples of ethyl cellulose microporous films made from ethyl cellulose and hydroxypropylcellulose (EC/HPC) polymer blends. LÄS MER

  2. 2. Interactionwise Semantic Awareness in Visual Relationship Detection

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Pagliarini Giovanni; Imtiaz Azfar; [2020-11-06]
    Nyckelord :Deep Learning; Natural Language Processing; Computer Vision; Visual Relationship Detection; Object Detection;

    Sammanfattning : Visual Relationship Detection (VRD) is a relatively young research area, where thegoal is to develop prediction models for detecting the relationships between objectsdepicted in an image. A relationship is modeled as a subject-predicate-object triplet,where the predicate (e.g an action, a spatial relation, etc. LÄS MER

  3. 3. Clustering and Classification of Time Series in Real-Time Strategy Games - A machine learning approach for mapping StarCraft II games to clusters of game state time series while limited by fog of war

    Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Olof Enström; Fredrik Hagström; John Segerstedt; Fredrik Viberg; Arvid Wartenberg; David Weber Fors; [2020-10-29]
    Nyckelord :Classification problem; Cluster analysis; Hierarchical clustering; Machine learning; Neural network; Random forest; Real-time strategy; StarCraft II; Time series;

    Sammanfattning : Real-time strategy (RTS) games feature vast action spaces and incomplete information,thus requiring lengthy training times for AI-agents to master them at the level of ahuman expert. Based on the inherent complexity and the strategical interplay betweenthe players of an RTS game, it is hypothesized that data sets of played games exhibitclustering properties as a result of the actions made by the players. LÄS MER

  4. 4. Effekter på nyckeltal i samband med implementeringen av IFRS 16

    Magister-uppsats, Göteborgs universitet/Företagsekonomiska institutionen

    Författare :Daniyal Askarnia; Alexander Fahlstad; [2020-09-08]
    Nyckelord :IAS 17; IFRS 16; leasegivare; leasetagare; operationell leasing; finansiell leasing; right-of-use assets; soliditet; skuldsättningsgrad; EBITDA-marginal; ROE; ROA; IAS 17; IFRS 16; lessor; lessee; operational leasing; financial leasing; right-of-use assets; solidity; leverage; EBITDA margin; ROE; ROA;

    Sammanfattning : Background and problem discussion: The previous leasing standard IAS 17 met criticismsince lessees have been able to classify their leases as either operational or financial. Thisoption reduced the comparability for the users of the financial reports, which increased therisk of misinterpreting the financial information. LÄS MER

  5. 5. A comparative study on the unsupervised classification of rat neurons by their morphology

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

    Författare :Sabrina Chowdhury; Added Kina; [2020]
    Nyckelord :;

    Sammanfattning : An ongoing problem regarding the automatic classification of neurons by their morphology is the lack of consensus between experts on neuron types. Unsupervised clustering using persistent homology as a descriptor for the morphology of neurons helps tackle the problem of bias in feature selection and has the potential of aiding neuroscience research in developing a framework for automatic neuron classification. LÄS MER