Search

Fall 2018

Sethi, Rameel

Music information retrieval (MIR), an interdisciplinary field involving the classifying or detection of structure in music, is essential for processing, indexing, querying and making recommendations from the vast amount of musical data available on the web and in audio library collections. Deep...

Fall 2020

Karami, Mahdi

This thesis considers some aspects of generative models including my contributions in deep probabilistic generative architectures and linear dynamical systems. First, some advances in deep probabilistic generative models are contributed. Flow-based generative modelling is an emerging and highly...

Fall 2024

Kushol, Rafsanjany

Deep learning (DL) has become a leading subset of machine learning (ML) and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards multi-center neuroimaging studies to...

Fall 2019

Sirota, Joshua

Emergent communication is a framework for machine language acquisition that has recently been utilized to train deep neural networks to develop shared languages from scratch and use these languages to communicate and cooperate. Previous work on emergent communication has utilized gradient-based...

Fall 2015

Burlet, Gregory D.

Music transcription is the process of extracting the pitch and timing of notes that occur in an audio recording and writing the results as a music score, commonly referred to as sheet music. Manually transcribing audio recordings is a difficult and time-consuming process, even for experienced...

Spring 2018

Hosseinzadeh Heydarabad,Sepideh

In this work we address the problem of fast shadow detection from single images of natural scenes. Different from traditional methods that employ expensive optimization methods, we propose a fast semantic-aware Convolutional Neural Network learning framework which trains on different kinds of...