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Full-Text Articles in Computer Engineering
Mitigation Of Catastrophic Interference In Neural Networks And Ensembles Using A Fixed Expansion Layer, Robert Austin Coop
Mitigation Of Catastrophic Interference In Neural Networks And Ensembles Using A Fixed Expansion Layer, Robert Austin Coop
Doctoral Dissertations
Catastrophic forgetting (also known in the literature as catastrophic interference) is the phenomenon by which learning systems exhibit a severe exponential loss of learned information when exposed to relatively small amounts of new training data. This loss of information is not caused by constraints due to the lack of resources available to the learning system, but rather is caused by representational overlap within the learning system and by side-effects of the training methods used. Catastrophic forgetting in auto-associative pattern recognition is a well-studied attribute of most parameterized supervised learning systems. A variation of this phenomenon, in the context of feedforward …
Online Multi-Stage Deep Architectures For Feature Extraction And Object Recognition, Derek Christopher Rose
Online Multi-Stage Deep Architectures For Feature Extraction And Object Recognition, Derek Christopher Rose
Doctoral Dissertations
Multi-stage visual architectures have recently found success in achieving high classification accuracies over image datasets with large variations in pose, lighting, and scale. Inspired by techniques currently at the forefront of deep learning, such architectures are typically composed of one or more layers of preprocessing, feature encoding, and pooling to extract features from raw images. Training these components traditionally relies on large sets of patches that are extracted from a potentially large image dataset. In this context, high-dimensional feature space representations are often helpful for obtaining the best classification performances and providing a higher degree of invariance to object transformations. …
An Expert System For Guitar Sheet Music To Guitar Tablature, Chuanjun He
An Expert System For Guitar Sheet Music To Guitar Tablature, Chuanjun He
Doctoral Dissertations
This project applies analysis, design and implementation of the Optical Music Recognition (OMR) to an expert system for transforming guitar sheet music to guitar tablature. The first part includes image processing and music semantic interpretation to interpret and transform sheet music or printed scores into editable and playable electronic form. Then after importing the electronic form of music into internal data structures, our application uses effective pruning to explore the entire search space to find the best guitar tablature. Also considered are alternate guitar tunings and transposition of the music to improve the resulting tablature.