Search for dissertations about: "CNNs"

Showing result 1 - 5 of 19 swedish dissertations containing the word CNNs.

  2. 1. Multi-LSTM Acceleration and CNN Fault Tolerance

    Author : Stefano Ribes; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Compression; SVD; LSTMs; CNNs; Fault Tolerance; Machine Learning; FPGA; Roofline Model; HLS; Caffe;

    Abstract : This thesis addresses the following two problems related to the field of Machine Learning: the acceleration of multiple Long Short Term Memory (LSTM) models on FPGAs and the fault tolerance of compressed Convolutional Neural Networks (CNN). LSTMs represent an effective solution to capture long-term dependencies in sequential data, like sentences in Natural Language Processing applications, video frames in Scene Labeling tasks or temporal series in Time Series Forecasting. READ MORE

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

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

    Abstract : 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. READ MORE

  5. 3. DeepMaker : Customizing the Architecture of Convolutional Neural Networks for Resource-Constrained Platforms

    Author : Mohammad Loni; Mikael Sjödin; Masoud Daneshtalab; Franz Pernkopf; Mälardalens högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Computer Science; datavetenskap;

    Abstract : Convolutional Neural Networks (CNNs) suffer from energy-hungry implementation due to requiring huge amounts of computations and significant memory consumption. This problem will be more highlighted by the proliferation of CNNs on resource-constrained platforms in, e.g., embedded systems. READ MORE

  6. 4. Geometric Supervision and Deep Structured Models for Image Segmentation

    Author : Måns Larsson; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; conditional random fields; convolutional neural networks; deep structured models; Semantic segmentation; self-supervised learning; supervised learning; semi-supervised learning;

    Abstract : The task of semantic segmentation aims at understanding an image at a pixel level. Due to its applicability in many areas, such as autonomous vehicles, robotics and medical surgery assistance, semantic segmentation has become an essential task in image analysis. READ MORE

  7. 5. Uncertainty-Aware Convolutional Neural Networks for Vision Tasks on Sparse Data

    Author : Abdelrahman Eldesokey; Michael Felsberg; Fahad Shahbaz Khan; Richard Bowden; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES;

    Abstract : Early computer vision algorithms operated on dense 2D images captured using conventional monocular or color sensors. Those sensors embrace a passive nature providing limited scene representations based on light reflux, and are only able to operate under adequate lighting conditions. READ MORE