Sökning: "CNN"

Visar resultat 1 - 5 av 170 uppsatser innehållade ordet CNN.

  1. 1. Malignant Melanoma Classification with Deep Learning

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Jakob Kisselgof; [2019]
    Nyckelord :Melanoma classification deep learning;

    Sammanfattning : Malignant melanoma is the deadliest form of skin cancer. If correctly diagnosed in time, the expected five-year survival rate can increase up to 97 %. Therefore, exploring various methods for early detection can contribute with tools which can be used to improve detection of disease and finally to make sure that help is given in time. LÄS MER

  2. 2. DSP Design With Hardware Accelerator For Convolutional Neural Networks

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Julian Hille; Lucas Santos Ferreira; [2019]
    Nyckelord :CNN; Hardware; Accelerator; DSP; Convolutional; Convolution; Neural; Network; Processor; Tensilica; FIR; Memory; SRAM; Technology and Engineering;

    Sammanfattning : Convolutional Neural Networks impressed the world in 2012 by reaching state-of-the-art accuracy levels in the ImageNet Large Scale Visual Recognition Challenge. The era of machine learning has arrived and with it countless applications varying from autonomous driving to unstructured robotic manipulation. LÄS MER

  3. 3. Detection of Archaeological Sites from Aerial Imagery using Deep Learning

    Master-uppsats, Lunds universitet/Institutionen för astronomi och teoretisk fysik

    Författare :Jorge Lazo; [2019]
    Nyckelord :Deep Learning; Archaeology; Computer Vision; Aerial Imagery; Transfer Learning.; Physics and Astronomy;

    Sammanfattning : In recent years, Deep Learning has proven to be an outstanding tool in the field of computer vision showing promising results in different fields such as the analysis of medical images, obstacle detection for self-driving cars, automatic image caption generation, etc. In the case of Archaeology, the adoption of these methods in the detection of archaeological structures from aerial images has been slower than in other fields. LÄS MER

  4. 4. Vision based facial emotion detection using deep convolutional neural networks

    Kandidat-uppsats, Mälardalens högskola/Akademin för innovation, design och teknik

    Författare :Fredrik Julin; [2019]
    Nyckelord :Computer vision; Deep learning; Convolutional neural network; CNN; Neural network; Machine learning; emotion detection; facial expression recognition; real-time; face detection;

    Sammanfattning : Emotion detection, also known as Facial expression recognition, is the art of mapping an emotion to some sort of input data taken from a human. This is a powerful tool to extract valuable information from individuals which can be used as data for many different purposes, ranging from medical conditions such as depression to customer feedback. LÄS MER

  5. 5. Traffic Sign Classification Using Computationally Efficient Convolutional Neural Networks

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Carl Ekman; [2019]
    Nyckelord :CNN; Machine Learning; Deep Learning; Computer Vision; Traffic Sign Recognition; Traffic Sign Classification; Image Classification; Neural Networks;

    Sammanfattning : Traffic sign recognition is an important problem for autonomous cars and driver assistance systems. With recent developments in the field of machine learning, high performance can be achieved, but typically at a large computational cost. LÄS MER