Sökning: "MobileNet"

Visar resultat 1 - 5 av 12 uppsatser innehållade ordet MobileNet.

  1. 1. Classification of Heart Views in Ultrasound Images

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :David Pop; [2020]
    Nyckelord :AI; deep learning; echocardiography; image classification;

    Sammanfattning : In today’s society, we experience an increasing challenge to provide healthcare to everyone in need due to the increasing number of patients and the shortage of medical staff. Computers have contributed to mitigating this challenge by offloading the medical staff from some of the tasks. LÄS MER

  2. 2. Using Convolutional Neural Networks to Detect People Around Wells in South Sudan

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Maria Kastberg; [2019]
    Nyckelord :Convolutional neural networks; Object detection; Transfer Learning; Image processing; Deep learning;

    Sammanfattning : The organization International Aid Services (IAS) provides people in East Africawith clean water through well drilling. The wells are located in surroundingsfar away for the investors to inspect and therefore IAS wishes to be able to monitortheir wells to get a better overview if different types of improvements needto be made. LÄS MER

  3. 3. Algorithm Design and Optimization of Convolutional Neural Networks Implemented on FPGAs

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Zekun Du; [2019]
    Nyckelord :Image Classification; Convolutional Neural Network; Top-1 Error; FPGA; Hardware Simulation; Bild Klassificering; Konvolutionellt neuralt nätverk; Top-1 Error; FPGA; Maskinvaru Simulering;

    Sammanfattning : Deep learning develops rapidly in recent years. It has been applied to many fields, which are the main areas of artificial intelligence. The combination of deep learning and embedded systems is a good direction in the technical field. LÄS MER

  4. 4. Model Distillation for Deep-Learning-Based Gaze Estimation

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Christos Matsoukas; [2019]
    Nyckelord :;

    Sammanfattning : With the recent advances in deep learning, the gaze estimation models reached new levels, in terms of predictive accuracy, that could not be achieved with older techniques. Nevertheless, deep learning consists of computationally and memory expensive algorithms that do not allow their integration for embedded systems. LÄS MER

  5. 5. Memory Efficient Semantic Segmentation for Embedded Systems

    Master-uppsats, Lunds universitet/Institutionen för datavetenskap

    Författare :Haochen Liu; Erik Olsson; [2019]
    Nyckelord :Neural networks; Semantic segmentation; Pruning; Quantization; Tiling; Memory allocation; DeepLab; MobileNet; Technology and Engineering;

    Sammanfattning : Convolutional neural networks (CNNs) have made rapid progress in the last years and in fields, such as computer vision, they are considered state-of-the-art. However, CNNs are very computationally intensive. This makes them challenging to use in embedded devices such as smartphones, security cameras and cars. LÄS MER