Sökning: "AlexNet"

Visar resultat 1 - 5 av 6 uppsatser innehållade ordet AlexNet.

  1. 1. Implementation of a Deep Learning Inference Accelerator on the FPGA.

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

    Författare :Shenbagaraman Ramakrishnan; [2020]
    Nyckelord :Artificial Intelligence; Machine Learning; Deep Learning; Neural Networks; Deep Learning Accelerators; NVDLA; FPGA; Technology and Engineering;

    Sammanfattning : Today, Artificial Intelligence is one of the most important technologies, ubiquitous in our daily lives. Deep Neural Networks (DNN's) have come up as state of art for various machine intelligence applications such as object detection, image classification, face recognition and performs myriad of activities with exceptional prediction accuracy. LÄS MER

  2. 2. Deep Learning Based Multi-Label Classification of Radiotherapy Target Volumes for Prostate Cancer

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Lina Welander; [2019]
    Nyckelord :Multi-label classification; MIQA; INCA; Deep neural network;

    Sammanfattning : An initiative to standardize the nomenclature in Sweden started in 2016 along with the creation of the local database Medical Information Quality Archive (MIQA) and a national radiotherapy register on Information Network for CAncercare (INCA). A problem of identifying the clinical tumor volume (CTV) structures and prescribed dose arose when the consecutive number, which is added to the CTV-name, was made inconsistently in MIQA and INCA. LÄS MER

  3. 3. A deep learning model for scene recognition

    Kandidat-uppsats, Mittuniversitetet/Institutionen för informationssystem och –teknologi

    Författare :Zhaoxin Meng; [2019]
    Nyckelord :Scene recognition; CNN; convolutional supervised; Fisher Vector; transfer learning;

    Sammanfattning : Scene recognition is a hot research topic in the field of image recognition. It is necessary that we focus on the research on scene recognition, because it is helpful to the scene understanding topic, and can provide important contextual information for object recognition. LÄS MER

  4. 4. An Investigation of Low-Rank Decomposition for Increasing Inference Speed in Deep Neural Networks With Limited Training Data

    Uppsats för yrkesexamina på avancerad nivå, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Victor Wikén; [2018]
    Nyckelord :deep neural networks; convolutional neural networks; AlexNet; inference speed; optimization; low-rank tensor decomposition; fine-grained classification problem; dog breed classification; transfer learning;

    Sammanfattning : In this study, to increase inference speed of convolutional neural networks, the optimization technique low-rank tensor decomposition has been implemented and applied to AlexNet which had been trained to classify dog breeds. Due to a small training set, transfer learning was used in order to be able to classify dog breeds. LÄS MER

  5. 5. Deep Learning Algorithms for Cardiac Image Classification and Landmark Detection

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Anton Holm; [2018]
    Nyckelord :Deep Learning; Machine Learning; Medical Image analysis; Image analysis; Deep Neural Networks; Mathematics and Statistics;

    Sammanfattning : With the increase in computational power, deep learning algorithms have become an active field of research over the last 7 years. These data-driven machine learning algorithms have produced good results in many applications, image analysis being one of them. LÄS MER