Sökning: "Convolutional Network"

Visar resultat 1 - 5 av 66 avhandlingar innehållade orden Convolutional Network.

1. 1. Convolutional Network Representation for Visual Recognition

   Författare :Ali Sharif Razavian; Atsuto Maki; Stefan Carlsson; Josephine Sullivan; Josef Sivic; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Convolutional Network; Visual Recognition; Transfer Learning; Computer Science; Datalogi;

   Sammanfattning : Image representation is a key component in visual recognition systems. In visual recognition problem, the solution or the model should be able to learn and infer the quality of certain visual semantics in the image. LÄS MER

3. 2. Network Parameterisation and Activation Functions in Deep Learning

   Författare :Martin Trimmel; Matematik LTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; deep learning; linear region; network parameterisation; activation function; network calibration; conformal predictnio; tropical algebra; rational function; temperature scaling; network symmetries;

   Sammanfattning : Deep learning, the study of multi-layered artificial neural networks, has received tremendous attention over the course of the last few years. Neural networks are now able to outperform humans in a growing variety of tasks and increasingly have an impact on our day-to-day lives. LÄS MER

4. 3. Deep Learning Methods for Classification of Glioma and its Molecular Subtypes

   Författare :Muhaddisa Barat Ali; Chalmers tekniska högskola; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; 1p 19q codeletion; generative adversarial network; convolutional neural network; glioma subtype classification; IDH mutation.; Deep learning; cycleGAN; convolutional autoencoder;

   Sammanfattning : Diagnosis and timely treatment play an important role in preventing brain tumor growth. Clinicians are unable to reliably predict LGG molecular subtypes from magnetic resonance imaging (MRI) without taking biopsy. Accurate diagnosis prior to surgery would be important. LÄS MER

5. 4. Deep Learning Methods for Classification of Gliomas and Their Molecular Subtypes, From Central Learning to Federated Learning

   Författare :Muhaddisa Barat Ali; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; glioma subtype classification; convolutional autoencoder; convolutional NN; multi-stream U-Net.; CycleGAN; 1p 19q codeletion; federated learning; IDH mutation; generative adversarial network; Deep learning;

   Sammanfattning : The most common type of brain cancer in adults are gliomas. Under the updated 2016 World Health Organization (WHO) tumor classification in central nervous system (CNS), identification of molecular subtypes of gliomas is important. LÄS MER

7. 5. Resource efficient automatic segmentation of medical images

   Författare :Minh Hoang Vu; Tommy Löfstedt; Tufve Nyholm; Anders Garpebring; Joakim Jonsson; Örjan Smedby; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; radiotherapy; medical imaging; deep learning; convolutional neural network; generative adversarial network; data augmentation; semantic segmentation; classification; activation map compression; radiofysik; radiation physics;

   Sammanfattning : Cancer is one of the leading causes of death worldwide. In 2020, there were around 10 million cancer deaths and nearly 20 million new cancer cases in the world. Radiation therapy is essential in cancer treatments because half of the cancer patients receive radiation therapy at some point. LÄS MER