Sökning: "Deep Layered Learning"

Hittade 3 avhandlingar innehållade orden Deep Layered Learning.

  1. 1. Network Parameterisation and Activation Functions in Deep Learning

    Författare :Martin Trimmel; Matematik LTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; deep learning; linear region; network parameterisation; activation function; network calibration; conformal predictnio; tropical algebra; rational function; temperature scaling; network symmetries;

    Sammanfattning : Deep learning, the study of multi-layered artificial neural networks, has received tremendous attention over the course of the last few years. Neural networks are now able to outperform humans in a growing variety of tasks and increasingly have an impact on our day-to-day lives. LÄS MER

  2. 2. Modeling Music : Studies of Music Transcription, Music Perception and Music Production

    Författare :Anders Elowsson; Anders Friberg; Pawel Herman; Anders Askenfelt; Gerhard Widmer; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Music Information Retrieval; MIR; Music; Music Transcription; Music Perception; Music Production; Tempo Estimation; Beat Tracking; Polyphonic Pitch Tracking; Polyphonic Transcription; Music Speed; Music Dynamics; Long-time average spectrum; LTAS; Algorithmic Composition; Deep Layered Learning; Convolutional Neural Networks; Rhythm Tracking; Ensemble Learning; Perceptual Features; Representation Learning;

    Sammanfattning : This dissertation presents ten studies focusing on three important subfields of music information retrieval (MIR): music transcription (Part A), music perception (Part B), and music production (Part C).In Part A, systems capable of transcribing rhythm and polyphonic pitch are described. LÄS MER

  3. 3. Reinforcement Learning of Locomotion based on Central Pattern Generators

    Författare :Cai Li; Tom Ziemke; Robert Lowe; Örjan Ekeberg; Linköpings universitet; []

    Sammanfattning : Locomotion learning for robotics is an interesting and challenging area in which the movement capabilities of animals have been deeply investigated and acquired knowledge has been transferred into modelling locomotion on robots. What modellers are required to understand is what structure can represent locomotor systems in different animals and how such animals develop various and dexterous locomotion capabilities. LÄS MER