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- 2Instrument transcription
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- 7Graduate and Postdoctoral Studies (GPS), Faculty of
- 7Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
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- 1Computing Science, Department of/Journal Articles (Computing Science)
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- 1Concordia University of Edmonton
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A finite element-convolutional neural network model (FE-CNN) for stress field analysis around arbitrary inclusions
Download2023-11-01
Rezasefat, Mohammad, Hogan, James D.
This study presents a data-driven finite element-machine learning surrogate model for predicting the end-to-end full-field stress distribution and stress concentration around an arbitrary-shaped inclusion. This is important because the model’s capacity to handle large datasets, consider...
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A Framework for Synthesis of Musical Training Examples for Polyphonic Instrument Recognition
DownloadFall 2018
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...
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Advances in Probabilistic Generative Models: Normalizing Flows, Multi-View Learning, and Linear Dynamical Systems
DownloadFall 2020
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...
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Deep learning based models for software effort estimation using story points in agile environments
Download2021-09-01
In the era of agile software development methodologies, traditional planning and software effort estimation methods are replaced to meet customer’s satisfaction in agile environments. However, software effort estimation remains a challenge. Although teams have achieved better accuracy in...
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Development of deep learning-based methods for rotating machinery fault diagnosis under varying speed conditions
DownloadSpring 2023
Rotating machines are widely used in industrial applications, such as driving motors in elevators and gearboxes in wind turbines. Machines in these applications often operate under varying speed conditions due to variable operation demand, ever-changing environment conditions and so on. As time...
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Fall 2019
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...
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Fall 2015
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...
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2017
Music transcription involves the transformation of an audio recording to common music notation, colloquially referred to as sheet music. Manually transcribing audio recordings is a difficult and time-consuming process, even for experienced musicians. In response, several algorithms have been...
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Prognostics and Maintenance Decision-making for Mechanical Systems based on Condition Monitoring Data
DownloadSpring 2024
Condition-based maintenance (CBM) is a maintenance approach that uses condition monitoring data to make maintenance decisions. The goal of CBM is to avoid machine shutdowns, reduce maintenance costs, and improve system safety. In modern mechanical systems, a wide range of sensors are used to...
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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...