Sökning: "image features"
Visar resultat 1 - 5 av 941 avhandlingar innehållade orden image features.
1. Representation Learning and Information Fusion : Applications in Biomedical Image Processing
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
2. Automatic Virus Identification using TEM : Image Segmentation and Texture Analysis
Sammanfattning : Viruses and their morphology have been detected and studied with electron microscopy (EM) since the end of the 1930s. The technique has been vital for the discovery of new viruses and in establishing the virus taxonomy. Today, electron microscopy is an important technique in clinical diagnostics. LÄS MER
3. Methods for Reliable Image Registration : Algorithms, Distance Measures, and Representations
Sammanfattning : Much biomedical and medical research relies on the collection of ever-larger amounts of image data (both 2D images and 3D volumes, as well as time-series) and increasingly from multiple sources. Image registration, the process of finding correspondences between images based on the affinity of features of interest, is often required as a vital step towards the final analysis, which may consist of a comparison of images, measurement of movement, or fusion of complementary information. LÄS MER
4. Adapting Deep Learning for Microscopy: Interaction, Application, and Validation
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. Spectral Image Processing with Applications in Biotechnology and Pathology
Sammanfattning : Color theory was first formalized in the seventeenth century by Isaac Newton just a couple of decades after the first microscope was built. But it was not until the twentieth century that technological advances led to the integration of color theory, optical spectroscopy and light microscopy through spectral image processing. LÄS MER