Sökning: "Deep Features"

Visar resultat 1 - 5 av 182 avhandlingar innehållade orden Deep Features.

1. 1. Deep Perceptual Loss and Similarity

   Författare :Gustav Grund Pihlgren; Marcus Liwicki; Fredrik Sandin; Hugo Larochelle; Luleå tekniska universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Image Similarity; Perceptual Similarity; Perceptual Loss; Deep Features; Deep Learning; Machine Learning; Maskininlärning;

   Sammanfattning : This thesis investigates deep perceptual loss and (deep perceptual) similarity; methods for computing loss and similarity for images as the distance between the deep features extracted from neural networks. The primary contributions of the thesis consist of (i) aggregating much of the existing research on deep perceptual loss and similarity, and (ii) presenting novel research into understanding and improving the methods. LÄS MER

3. 2. Deep Evidential Doctor

   Författare :Awais Ashfaq; Sławomir Nowaczyk; Mark Dougherty; Cristina Soguero Ruiz; Högskolan i Halmstad; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

   Sammanfattning : Recent years have witnessed an unparalleled surge in deep neural networks (DNNs) research, surpassing traditional machine learning (ML) and statistical methods on benchmark datasets in computer vision, audio processing and natural language processing (NLP). Much of this success can be attributed to the availability of numerous open-source datasets, advanced computational resources and algorithms. LÄS MER

4. 3. Learning Spatiotemporal Features in Low-Data and Fine-Grained Action Recognition with an Application to Equine Pain Behavior

   Författare :Sofia Broomé; Hedvig Kjellström; Efstratios Gavves; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Equine pain; computer vision for animals; deep learning; deep video models; spatiotemporal features; video understanding; action recognition; frame dependency; video data; end-to-end learning; temporal modeling; Datalogi; Computer Science;

   Sammanfattning : Recognition of pain in animals is important because pain compromises animal welfare and can be a manifestation of disease. This is a difficult task for veterinarians and caretakers, partly because horses, being prey animals, display subtle pain behavior, and because they cannot verbalize their pain. LÄS MER

5. 4. Pith location and annual ring detection for modelling of knots and fibre orientation in structural timber : A Deep-Learning-Based Approach

   Författare :Tadios Habite; Anders Olsson; Osama Abdeljaber; Jan Oscarsson; Welf Löwe; Julie Cool; Linnéuniversitetet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Sawn timber; Pith location; Deep learning; Artificial neural networks; Convolutional neural network; Conditional generative adversarial network; Knot detection; Knot modelling; Knot reconstruction; Fibre orientation; Annual ring profile; Byggteknik; Civil engineering;

   Sammanfattning : Detection of pith, annual rings and knots in relation to timber board cross-sections is relevant for many purposes, such as for modelling of sawn timber and for real-time assessment of strength, stiffness and shape stability of wood materials. However, the methods that are available and implemented in optical scanners today do not always meet customer accuracy and/or speed requirements. LÄS MER

7. 5. Self-supervised deep learning and EEG categorization

   Författare :Mats Svantesson; Magnus Thordstein; Håkan Olausson; Anders Eklund; Gerald Cooray; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; EEG; Deep Learning; Self-supervised; Interrater Agreement; T- SNE;

   Sammanfattning : Deep learning has the potential to be used to improve and streamline EEG analysis. At the present, classifiers and supervised learning dominate the field. Supervised learning depends on target labels which most often are created by human experts manually classifying data. LÄS MER