Sökning: "image classification"

Visar resultat 1 - 5 av 379 avhandlingar innehållade orden image classification.

  1. 1. Representation Learning and Information Fusion : Applications in Biomedical Image Processing

    Författare :Elisabeth Wetzer; Nataša Sladoje; Fred Hamprecht; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Representation Learning; Texture Descriptors; Equivariant Neural Networks; Contrastive Learning; Image Classification; Image Registration; Image Retrieval; Digital Pathology; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : In recent years Machine Learning and in particular Deep Learning have excelled in object recognition and classification tasks in computer vision. As these methods extract features from the data itself by learning features that are relevant for a particular task, a key aspect of this remarkable success is the amount of data on which these methods train. LÄS MER

  3. 2. A path along deep learning for medical image analysis : With focus on burn wounds and brain tumors

    Författare :Marco Domenico Cirillo; Anders Eklund; Veronika Cheplygina; Linköpings universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep learning; Medical image analysis; Burn wounds; Brain tumors; Image classification; Image segmentation; Image augmentation; CNNs; GANs;

    Sammanfattning : The number of medical images that clinicians need to review on a daily basis has increased dramatically during the last decades. Since the number of clinicians has not increased as much, it is necessary to develop tools which can help doctors to work more efficiently. LÄS MER

  4. 3. Adapting Deep Learning for Microscopy: Interaction, Application, and Validation

    Författare :Ankit Gupta; Carolina Wählby; Ida-Maria Sintorn; Ola Spjuth; Andreas Hellander; Philip Kollmannsberger; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Microscopy; Human-in-the-Loop; Semi-Supervised Learning; Application-Specific Analysis; Image Classification; Image-to-Image Translation; Template Matching; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : Microscopy is an integral technique in biology to study the fundamental components of life visually. Digital microscopy and automation have enabled biologists to conduct faster and larger-scale experiments with a sharp increase in the data generated. LÄS MER

  5. 4. Computerized Cell and Tissue Analysis

    Författare :Azadeh Fakhrzadeh; Gunilla Borgefors; Cris Luengo Hendriks; Lena Holm; Nasir Rajpoot; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Image processing; Cell; Tissue; Segmentation; Classification; Histology; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : The latest advances in digital cameras combined with powerful computer software enable us to store high-quality microscopy images of specimen. Studying hundreds of images manually is very time consuming and has the problem of human subjectivity and inconsistency. LÄS MER

  7. 5. Automated Tissue Image Analysis Using Pattern Recognition

    Författare :Jimmy Azar; Anders Hast; Ewert Bengtsson; Martin Simonsson; Marco Loog; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; tissue image analysis; pattern recognition; digital histopathology; immunohistochemistry; paired antibodies; histological stain evaluation; Computerized Image Processing; Datoriserad bildbehandling;

    Sammanfattning : Automated tissue image analysis aims to develop algorithms for a variety of histological applications. This has important implications in the diagnostic grading of cancer such as in breast and prostate tissue, as well as in the quantification of prognostic and predictive biomarkers that may help assess the risk of recurrence and the responsiveness of tumors to endocrine therapy. LÄS MER