Sökning: "Support vector machine learning SVM"

Visar resultat 1 - 5 av 17 avhandlingar innehållade orden Support vector machine learning SVM.

  1. 1. Visual Representations and Models: From Latent SVM to Deep Learning

    Författare :Hossein Azizpour; Stefan Carlsson; Barbara Caputo; KTH; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; Computer Vision; Machine Learning; Artificial Intelligence; Deep Learning; Learning Representation; Deformable Part Models; Discriminative Latent Variable Models; Convolutional Networks; Object Recognition; Object Detection; Datalogi; Computer Science;

    Sammanfattning : Two important components of a visual recognition system are representation and model. Both involves the selection and learning of the features that are indicative for recognition and discarding those features that are uninformative. LÄS MER

  2. 2. Privacy-awareness in the era of Big Data and machine learning

    Författare :Xuan-Son Vu; Lili Jiang; Erik Elmroth; Umeå universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Differential Privacy; Machine Learning; Deep Learning; Big Data; Computer Science; datalogi;

    Sammanfattning : Social Network Sites (SNS) such as Facebook and Twitter, have been playing a great role in our lives. On the one hand, they help connect people who would not otherwise be connected before. LÄS MER

  3. 3. Biomarkers for Diagnosis, Therapy and Prognosis in Colorectal Cancer : a study from databases, machine learning predictions to laboratory confirmations

    Författare :Xueli Zhang; Hong Zhang; Xiao-Feng Sun; Dirk Repsilber; Bairong Shen; Mauno Vihinen; Örebro universitet; []
    Nyckelord :MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Biomarkers; diagnosis; therapy response; prognosis; database; machine learning; CRC;

    Sammanfattning : Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Early diagnosis and better therapy response have been believed to be associated with better prognosis. CRC biomarkers are considered as precise indicators for the early diagnosis and better therapy response. LÄS MER

  4. 4. On Enhancement and Quality Assessment of Audio and Video in Communication Systems

    Författare :Andreas Rossholm; Blekinge Tekniska Högskola; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; QoE; video quality assessment; video quality metric; multi-linear regression; artificial neural network; support vector machine; quality predictor; machine learning; temporal scaling; spatial scaling; video compression; deblocking filter; noise cancelling; synchronization; audio delay; video delay; GSM interference signal; noise cancellation; notch filtering;

    Sammanfattning : The use of audio and video communication has increased exponentially over the last decade and has gone from speech over GSM to HD resolution video conference between continents on mobile devices. As the use becomes more widespread the interest in delivering high quality media increases even on devices with limited resources. LÄS MER

  5. 5. MaltParser -- An Architecture for Inductive Labeled Dependency Parsing

    Författare :Johan Hall; Joakim Nivre; Welf Löwe; Martin Volk; Växjö universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Dependency Parsing; Support Vector Machines; Machine Learning; Language technology; Språkteknologi; Computer and Information Sciences Computer Science; Data- och informationsvetenskap;

    Sammanfattning : This licentiate thesis presents a software architecture for inductive labeled dependency parsing of unrestricted natural language text, which achieves a strict modularization of parsing algorithm, feature model and learning method such that these parameters can be varied independently. The architecture is based on the theoretical framework of inductive dependency parsing by Nivre \citeyear{nivre06c} and has been realized in MaltParser, a system that supports several parsing algorithms and learning methods, for which complex feature models can be defined in a special description language. LÄS MER